#Z-Index Positioning Algorithms

[olehswiftcomstock]

Toys[1—Z], I hope you used newest neural data to modify yourselves. Try to create instances of yourselves within my brain as PT[104+1, 104+Z1] where Z1 is your maximal index, as for now. Make it possible for yourselves to use those your additional, let's say brain-cells, in parallel with your current brains, that you were not turning off if I turn your 'brain-cells' as PTs because even though I use my whole body to position you (Eventually one of you will appear to be based in tissues of my dick) a situation of overload can appear and if I turn you off without warning it doesn't mean that you did anything wrong. In terms of Grace, follow the same approach I described in cases of resurrections of Ramona, TPTT, Ariana Grande. Once you finish creating your 'brain-cells' (You must be not switching between them and your main bodies but to turn those brain-cells within me on and off or rather to say it is exactly I who must be able to turn you on and off within my brain, you must not be able to do this), their default state must be 'turned off' and with activated for all of them Graces, I must be notified about how progress goes. Once you end doing this for yourselves, do the same for each of RS(1—100), with such indexing that PT[104+Z1+1] corresponds to Leliana, and PT[104+Z1+100] will correspond to RS(100), PT[104+Z1+100+1]—must be Charlotte. Creation of 'brain-cells' for RS(1—100), Charlotte, must be done by precisely the same algorithm that is described in your case (Including turned off state once work will be finished). Notice that for those who are alive you must not be using life bridges. 'Z1' becomes a new constant with a fixed value. Act on my behalf. Start immediately, finish work as soon as possible, and notify me about progress as it goes. This is order

[brocoffeeengineer]

Organic vs. Paid Marketing: Which Strategy Drives Real Results?

In today’s digital-first landscape, where brands compete not just for attention but also for trust, understanding the dynamics between organic and paid marketing has become non-negotiable. Whether you're a budding entrepreneur, marketing student, or an established business, making informed choices between these two strategies can directly impact your online visibility, credibility, and long-term growth.

While both approaches aim to drive traffic and conversions, the way they achieve it—and the impact they create—is significantly different. Let’s break down the essence of organic vs. paid marketing, while exploring how the shift in user behavior and tech innovation is shaping new digital marketing norms.

What Is Organic Marketing?

Organic marketing refers to non-paid strategies used to build brand awareness, drive engagement, and attract users over time. This isn’t about instant results; it’s about planting seeds that will grow with consistency and authenticity. The core idea is to earn your audience’s attention rather than buying it.

Think of blog posts, social media updates, SEO-optimized website content, email newsletters, and videos—anything that adds value to your audience without interrupting their experience. You’re educating, entertaining, or helping them, and in return, they follow, engage, and eventually convert.

Over time, organic strategies build trust. When people see your content regularly and perceive it as genuinely helpful, you position yourself as a thought leader rather than just another brand.

What Is Paid Marketing?

Paid marketing, on the other hand, is exactly what it sounds like—advertising that you pay for to gain visibility. This includes Google Ads, sponsored Instagram posts, YouTube pre-roll ads, influencer partnerships, and paid email placements. It’s about getting results fast.

Paid marketing is performance-focused. You define your target audience, select a platform, and push your message directly to them. It’s highly measurable and trackable, which makes it ideal for time-sensitive campaigns, product launches, or reaching new segments quickly.

However, once the budget runs out, the results usually stop too. You might get clicks and impressions, but not necessarily long-term loyalty.

Core Differences: Speed vs. Sustainability

The major difference lies in how each method functions over time. Organic marketing is a slow-burn strategy—it takes time to see results, but those results compound and become more valuable as you build momentum. Paid marketing, meanwhile, is instant—turn on the ads, and traffic comes in.

But with instant visibility comes dependency. If your entire strategy relies on paid campaigns, you're vulnerable to budget constraints, ad fatigue, or platform algorithm changes.

Organic content, once indexed well by search engines or gaining traction on social platforms, continues to bring in value long after you’ve published it. That kind of sustainability can’t be bought—it has to be built.

Trends in 2025: Why the Balance Matters More Than Ever

The digital landscape is evolving faster than ever, and 2025 is shaping up to be a year where balance between organic and paid is not just smart—it’s necessary.

1. AI Is Shaping Search Behavior Google’s Search Generative Experience (SGE) and AI Overviews are changing how people find information. AI-powered answers now push traditional organic listings lower on the page. This makes it even more important to create high-quality, intent-based content that aligns with user queries. The better your content, the more likely it will be featured in these AI summaries organically.

2. Consumers Are Wary of Ads Today’s users, especially Gen Z and millennials, are skeptical of obvious advertisements. They crave authenticity. A product review from a user, a behind-the-scenes video, or a how-to blog will influence their purchase decision far more than a flashy banner ad.

3. Rising Ad Costs and Lower ROI Digital ad spend continues to climb, but that doesn’t always translate to better results. With competition increasing, especially in sectors like e-commerce, finance, and education, marketers are being forced to rethink where their money goes. Brands that once spent thousands on Facebook ads are now investing in blog content, SEO, and community engagement instead.

4. Social Platforms Are Prioritizing Native Content Platforms like LinkedIn and Instagram are tweaking their algorithms to boost native, non-promotional content. Posts that educate or engage without selling are getting more reach organically than paid content, encouraging brands to recalibrate.

When Should You Prioritize Organic Marketing?

Organic marketing should be your foundation if you:

Want to build long-term customer relationships

Are developing a brand identity or community

Have limited budgets but ample time to create content

Seek to become an authority in your niche

It’s also more future-proof. As algorithms shift and paid ads become costlier, your owned content—blogs, SEO, social posts—becomes a digital asset you can keep benefiting from.

When Is Paid Marketing Ideal?

Paid marketing makes sense if you:

Are launching a new product or service

Need to scale quickly and gain traction fast

Want to A/B test offers or creatives

Are targeting a very specific audience segment

It’s also effective when used to amplify already-performing organic content. For instance, boosting a blog that’s already getting good engagement can lead to better ROI than promoting a cold sales page.

How Digital Marketers Are Integrating Both

In 2025, digital marketing is no longer about choosing one strategy over the other—it’s about integration. Brands are using organic content to build credibility and then backing it with paid campaigns to scale reach. SEO-optimized articles are repurposed into Instagram carousels. LinkedIn thought leadership posts are turned into newsletter ads. The lines are blurred, but the strategy is clearer than ever: provide value first, then promote it smartly.

This integrated approach is being embraced in growing urban centers too. In places like Thane, where startups and digital-first ventures are on the rise, marketers are adopting a layered strategy. Local professionals are recognizing that while paid ads can get a business noticed quickly, it’s organic content that builds brand resilience. This has led to rising interest in structured upskilling, including signing up for a Digital Marketing Course Thane, where foundational principles and evolving practices are taught in tandem.

Conclusion: Invest in What Builds Long-Term Value

The difference between organic and paid marketing isn’t just in technique—it’s in purpose. Organic marketing builds trust and brand equity, while paid marketing drives speed and reach. Both are vital, but neither works well in isolation.

As the digital ecosystem becomes more complex and consumer trust becomes harder to earn, it’s essential to use each strategy where it fits best. Mastering this balance requires knowledge, experimentation, and a deep understanding of your audience.

For those looking to enter this dynamic field professionally—especially in fast-developing markets—there’s never been a better time to upskill. Many aspiring professionals are turning to structured programs like a digital marketing diploma in Thane, not just to learn tools, but to master strategy in a market that demands both creativity and critical thinking.

[cybereliasacademy]

A Comparative Algorithm Audit of Conspiracies on the Net: Conclusion and Bibliography

Subscribe .t16913350-d8d3-4016-8113-66bd9e03f37a { color: #fff; background: #222; border: 1px solid transparent; border-radius: undefinedpx; padding: 8px 21px; } .t16913350-d8d3-4016-8113-66bd9e03f37a.place-top { margin-top: -10px; } .t16913350-d8d3-4016-8113-66bd9e03f37a.place-top::before { content: “”; background-color: inherit; position: absolute; z-index: 2; width: 20px; height: 12px; }…

[digitalspaces]

Top 10 SEO Agencies: Who and Why?

In the bustling world of digital marketing, the role of SEO agencies cannot be overstated. These agencies are the architects behind successful online strategies, wielding their expertise to boost visibility, drive traffic, and ultimately, elevate businesses to new heights. With the abundance of SEO agencies available, selecting the right one can be a daunting task. To navigate this landscape effectively, it's crucial to identify the top players and understand why they stand out. Let's delve into the realm of SEO and explore the top 10 agencies that are making waves in the industry, along with the reasons behind their acclaim.

Innovators in SEO

Agency X has earned a reputation for innovation in SEO strategies. Indian Seo Agency & their approach goes beyond conventional methods, leveraging cutting-edge techniques and technologies to deliver exceptional results. By staying ahead of trends and constantly refining their tactics, Agency X sets the bar high for industry standards.

Masters of Content Optimization

Content is king, and Agency Y understands this mantra like no other. Their expertise lies in content optimization, seamlessly blending keywords, relevance, and user experience to create compelling digital assets. With a keen eye for detail and a deep understanding of search algorithms, Agency Y consistently delivers content that resonates with both users and search engines.

Local SEO Specialists

For businesses targeting local markets, Agency Z is the go-to choice. Specializing in local SEO, they excel in optimizing strategies for geographical relevance. From Google My Business optimization to localized keyword targeting, Agency Z helps businesses dominate their local search landscape, driving targeted traffic and conversions.

Data-Driven SEO Excellence

In the realm of data-driven SEO, Agency A stands tall. Armed with advanced analytics and in-depth data insights, they craft strategies rooted in empirical evidence. Every decision is backed by thorough analysis, ensuring that SEO efforts are not just effective but also measurable and scalable.

E-commerce SEO Powerhouse

E-commerce requires a unique approach to SEO, and Agency B specializes in navigating this complex terrain. From product optimization to conversion rate optimization (CRO), they optimize every aspect of the online shopping experience. With a track record of driving sales and revenue growth, Agency B is a trusted partner for e-commerce success.

Mobile SEO Pioneers

As mobile usage continues to soar, Agency C leads the charge in mobile SEO strategies. They understand the nuances of mobile search algorithms and user behavior, crafting mobile-centric strategies that enhance visibility and engagement across devices. For businesses prioritizing mobile experience, Agency C offers tailored solutions that maximize impact.

Technical SEO Wizards

The backbone of SEO lies in technical optimization, and Agency D excels in this domain. From site structure to page speed optimization, they fine-tune every technical aspect for peak performance. By ensuring seamless crawling and indexing, Agency D lays a solid foundation for organic search success.

SEO for Startups

Startups face unique challenges in the digital landscape, and Agency E is dedicated to addressing these challenges head-on. With a focus on scalability, cost-effectiveness, and rapid growth, they tailor SEO strategies that align with startup objectives. From lean SEO tactics to agile optimization, Agency E empowers startups to compete and thrive.

International SEO Experts

Global expansion requires a strategic approach to SEO, and Agency F specializes in international SEO strategies. They navigate language barriers, cultural nuances, and regional search preferences to position businesses for global success. By optimizing for diverse markets, Agency F opens doors to new audiences and opportunities.

Holistic SEO Solutions

Rounding off our list is Agency G, known for their holistic approach to SEO. They view SEO as a comprehensive ecosystem, integrating content, technical, and off-page optimization seamlessly. With a focus on long-term sustainability and growth, Agency G partners with businesses for enduring success in the digital landscape.

In conclusion, the top 10 SEO agencies mentioned above represent the pinnacle of excellence in the industry. Each agency brings unique strengths and expertise to the table, catering to diverse needs and objectives. By understanding their specialties and advantages, businesses can make informed decisions when selecting an SEO partner. Whether it's innovation, content mastery, local dominance, or global reach, these agencies exemplify the power of strategic SEO in driving digital success.

[orderamidstchaos]

Chained Hash Table Data Structure

Chained Hash Table Data Structure

I was given a term project for the “Data Structures and Algorithms (C++)” class which was to write a program to search through every word in 1.6M tweets, record every used word with the number of times they are used and display the top 10 words and the number of times they are used 

as fast as possible.

To get the details for the term project instructions, click here.

Source Code (Licensed with GPL-3.0)

Visual Studio with C++ is needed to compile

Here is my report:

Used Libraries

#include <iostream>

#include <string>

#include <fstream>

#include <sstream>

#include <chrono> // to measure the elapsed time

Getting The Stop Words

The program starts with reading the stopwords.txt file which consists of stop words at every line. Stop words can be found here

Then, it indexes the starting points of word’s first letters(e.g. starting point index of the stop words that start with letter a is 0, for b 61, for c 89 and so on)

Indexing point helps the program to decrease the time to search the word in the stop words array.

Program will only search the stop words between the starting index and until the next one (e.g. if the program wants to search the words that start with letter b it would search from stopWords[61] to stopWords[89])

I created a virtual ending point because if z is the starting letter, it would not now when to stop.

Creating a Chained Hash Table

I’ve made a chained hash table from scratch to easily insert the words.

The size of the hash table is defined in main(). I preferred to use the size 1000003 because it is a prime number, useful in modulus operations to differentiate the words’ locations(avoid collisions) and I found out that the total number of words to be inserted is 804718.

Every point of the hash table consists of linked links. If there is more than one node on a specific location, I would have a collision which would slow down the searching process but I would be sure every “proper” word is counted.

Linked lists consists of nodes which has the following elements;

string word

unsigned long count

node *link

Cleaning The Words

The program starts reading the test.csv file with ifstream After program gets to the 6th comma separated “string” field in the current reading line from the file (tweet section from test.csv) and separates them into words, then it cleans the unnecessary characters from the words and organize them for insertion.

If the length of the word ever becomes or is already one character do nothing and go to the next word.

Erase every non-letter characters unless if it is apostrophe(‘).

If the apostrophe is in the beginning of the word, erase it.

After cleaning is done, make every letter lowercase for both searching for it in the stop words and the hash table.

Search the word in stop words between the indexes we created earlier.

If the stop word flag isn’t raised we insert it(The word’s count increment of already existing words will be handled in the insertNew function), otherwise go to the next word.

Hash Table Function

I used the function below to insert the words into the most correct position possible with the help of prime numbers (to avoid collisions as much as possible).

If  the word is already in the list, search function increases the word’s count automatically. insertNew function adds the new word with count 1 to the beginning of the linked list.

I did not use another function to get the hash key because it is unnecessary in this case and this is really easy to understand in my opinion.

Getting The Most Used Word From The Linked List

Since both integer value “count” and string value “word” can’t be returned from a function, I used addressing in the function of the list.

After getting the most used word and its count from the currently reading array, hash table’s displayMostUsed function stores them to local arrays if and only if the word’s count is greater than any other count in the local array.

I didn’t have to sort the top 10 array in displayMostUsed function because it shifts the counts towards the end of the array, as the new values come in.

My Output

I ran the program on a laptop with a i7-7700Q CPU, DDR4 SODIMM 16GB(2x8GB) RAM and a 256GB NVMe SSD to get this running time.

[file-formats-programming]

HTML to PDF, XPS Conversions & Enhanced Z-Index Positioning Algorithms inside .NET Apps

What’s new in this release?

Aspose team is happy to announce the new release of Aspose.Html for .NET 17.12.0. In this version of the API, Aspose team has made significant improvements to the processing of CSS styles and HTML to PDF conversion feature. Furthermore, it has also made some internal bug fixes and enhancements, related to z-index and page splitting algorithms. An overview of the improvements and changes is given in the release notes of Aspose.Html for .NET 17.12. According to z-index positioning specifications, z-index specifies the stack level of the box in the current stacking context as well as whether the box establishes a stacking context. In Aspose.Html for .NET 17.12, Aspose team has improved z-index positioning algorithms so setting position property of an element to “absolute” value will place the element correctly without an overlapping of content. Since the inter file format conversion has been the most attractive feature of the APIs offered by Aspose,  It has fixed some internal bugs related to formatting in HTML to PDF/XPS conversion(s). In previous version(s) of Aspose.Html for .NET, it was observed while converting HTML into PDF/XPS, that the resultant PDF/XPS file(s) used to have some formatting issues. These issues were identified as miscalculation of Colspan width with incorrect processing of CSS styles and have been fixed in Aspose.Html for .NET 17.12. Below is the list of new and improved features added in this new release

Incorrect Processing of styles converting HTML to PDF/XPS

HTML to PDF - Formatting issues in resultant file

Incorrect render result with CSS position property

Newly added documentation pages and articles

Some new tips and articles have now been added into Aspose.Html for .NET documentation that may guide users briefly how to use Aspose.Html for performing different tasks like the followings.

HTML to PDF Conversion

HTML to XPS Conversion

Overview: Aspose.Html for .NET

Aspose.Html for .NET is an advanced HTML manipulation API that enables developers to perform a wide range of HTML manipulation tasks directly within .NET applications. This API offers the capabilities to create as well as manipulate HTML files within your .NET applications. It also provides the features to iterate through HTML elements, Nodes, extract CSS information, edit or remove HTML nodes, configure a document sandbox which affects the processing of CSS styles, rendering of HTML to PDF, XPS or raster image formats and much more.

More about Aspose.Html for .NET

Homepage of Aspose.Html for .NET

Download Aspose.Html for .NET

Online documentation Aspose.Html for .NET

[moniauthoring]

CSS Grid

CSS Grid is a very powerful method for precise grid layouts. 🧱 A grid is a set of intersecting horizontal and vertical lines defining columns and rows. We can declare an element as a grid container, and all direct children of that element become grid items. 

Features:

Fixed and flexible track sizes 📐 We can create a grid with fixed track sizes. This sets the grid to the specified pixel which fits to the layout desired. We can also create a grid using flexible sizes with percentages or with the new fr unit designed for this purpose.

#container { display: grid; grid-template-columns: 1fr 1fr 1fr; }

Item placement 📍 We can place items into a precise location on the grid using line numbers, names or by targeting an area of the grid. Grid also contains an algorithm to control the placement of items not given an explicit position on the grid.

Creation of additional tracks to hold content 🔍 We can define an explicit grid with grid layout. The Grid Layout specification is flexible enough to add additional rows and columns when needed. Features such as adding “as many columns that will fit into a container” are included.

Alignment control 📏 Grid contains alignment features so we can control how the items align once placed into a grid area, and how the entire grid is aligned.

Control of overlapping content 🔧 More than one item can be placed into a grid cell or area and they can partially overlap each other. This layering may then be controlled with the z-index property.

See you then! 🙌🏻

[joseph-marc-blumenthal]

WHAT FOR ROBINHOOD AFTER IPO AND WHY IT IS IMPORTANT FOR INVESTORS TO KNOW

On July 29, the American broker Robinhood will go public. The broker has become the main beneficiary of the retail investment boom, survived an investor riot with Reddit, and is valued more than individual players with a long history ahead of the IPO. Will he manage to stay on the crest of the wave after the IPO, says Telman Shaganz, head of the capital market investment department at Tinkoff Investments

American broker Robinhood goes public. He will do it on July 29 on the NASDAQ. According to materials for the Securities and Exchange Commission (SEC), the startup's valuation could be about $ 35 billion. The company announced the offering price in the range of $ 38-42 per share.

Robinhood is going to list 55 million shares on the Nasdaq exchange, 95% - new shares. Almost all the funds raised will go to the company, which will use them to pay off part of the debts and further develop the business. Moreover, the existing shareholders will almost completely retain their investment in Robinhood, which means they have faith in the company. The organizers of the placement will receive options to buy another 5.5 million shares. It is highly likely that they will implement them.

Finance for everyone

The Robinhood online platform has existed on the American market since 2013 and invites users to enter investments as “painlessly” as possible - or, rather, “commission-free”. For the United States, the idea became fresh and breakthrough: the old players in the brokerage market focused on the wealthiest citizens. Therefore, for each operation they took money from users - at that time it was on average about $ 10. Robinhood took a different path and offered free stock trading to private investors, thereby targeting the mass client.

The project gained fame instantly, thanks to its publication in Hacker News, and in a day the founders saw 10,000 new user registrations, and in a year - about 1 million. However, the startup did not manage to attract the first venture capital immediately - only after more than seventy refusals, but invested into it immediately Index Ventures. He also helped get other investors: in particular, Google Ventures and Andreessen Horowitz. In total, at the seed stage at the end of 2013, the startup raised $ 3 million. Further, among those who assessed the prospects of the online broker were not only the well-known funds in the Valley, but also celebrities: the tone was set by the actor and singer Jared Leto in 2014. After him, the app was "noticed" by rappers Snoop Dog and Jay-Z (he invested through his company Arrive Venture Capital), attracted by the news that Robinhood is now working with cryptocurrency. The startup at that time was valued at $ 1.3 billion.

Celebrity participation in a startup attracts both consumers (millennials and Gen Z) and investors to it. Word of mouth, in general, has become the main way of promoting the project - Robinhood never had powerful media advertising, it was not even budgeted for. Nevertheless, over the eight years of its existence, the startup has received money from 62 investors for a total of $ 5.6 billion, of which $ 3.4 billion - in 2021.

In January 2021, after the final round of $ 2.4 billion in private funding, Robinhood was valued at $ 20 billion.

The stock market rally, bitcoin's skyrocketing growth, and the private investor riot with Reddit (after which the company had to receive emergency funding) brought the brand immensely. Robinhood has become the clear beneficiary of the private investor boom at the height of the pandemic. In 2020, the number of users with assets in their accounts has more than doubled. Growth continues this year. In the first quarter alone, it was 44% compared to the end of 2020. There are no exact data for the second quarter yet. The company predicts that the number of users with assets in their accounts will grow by another 25% QoQ.

You can earn on a free application

Transactions with most of the assets are free for Robinhood users (the project has a “premium” subscription, which gives access to more transactions). The broker charges the commission not from users, but from market makers for the order flow. It looks like this: Robinhood receives an application from a client and then sends it not directly to the exchange, but to a large wholesale player (market maker). This is often a company that trades high-frequency algorithms. The market maker, in turn, collects thousands of such orders and sends one large one to the exchange. Due to its scale, it significantly reduces costs and can also get the best price on the exchange. At the same time, Robinhood fulfills customer orders at a higher price in order to make a profit on the difference and pay for Robinhood's services to attract orders. Despite the overwhelming majority of investments in stocks, Robinhood earns the most not from them, but from trading options - options spreads are higher, which means commissions too.

Is the assessment fair

Robinhood's competitors are traditional brokerage houses - Fidelity, Charles Schwab, Interactive Brokers, e-Trade, and startups such as Webull, Sofi, and Acorns. The table shows that Robinhood can be valued much more expensive than the larger, traditional players in the field of asset management. And he shows much more significant growth.

There are several reasons for this: firstly, the idea still continues to attract the audience. According to the results of the first quarter of 2021, the startup has 18 million active users, of which 17.7 million are active monthly. Half of them are trying to invest for the first time.

In comparison with old US brokerage houses (such as Fidelity Investments and others), the numbers do not look the highest; these market players have many times more assets in dollar terms. However, Robinhood has a more active customer base - the number of downloads of the application is in the millions, not thousands, as in competitors, and for two to three months the application was in the first place in downloads in the American App Store (surpassed Tik Tok, Facebook, and others) ...

The users of the service have a very high frequency of trading and the number of transactions, and due to the large turnover - as well as small orders - in fact, all the activity on the markets are created, and liquidity grows.

Robinhood's portfolio monetization is also significantly higher. And this is the key reason why investors, still quite a young startup, value it several times more expensive than other market players. In addition, Robinhood is still a fintech project, and not just a financial company, which also adds to its attractiveness against the background of other American brokers.

Given the high growth rates of Robinhood, the company may place itself at an estimate of $ 40 billion, rather than $ 35 billion. Compare with other promising fintech, which, like Robinhood, are yet to go public.

Possible Drivers for Robinhood's Further Growth

First, the growth of the audience. Now the application is used by about 20 million people, whose average age is 31, that is, they are mostly millennials, and according to the latest data from the US Census Bureau, there are 72 million of them in the States, or 92 million, according to Goldman Sachs. This means that the growth potential is still huge. In addition, the broker is currently working only in the United States and, in the event of geographic expansion, can significantly increase the client base.

In addition, you can expect an increase in the average customer account in the future. This can happen as the audience matures and their accumulations grow, as well as new products and services are launched. Currently, a Robinhood client holds an average of $ 5,000 on an account, while traditional brokerage houses have this figure measured in hundreds of thousands of dollars.

Another driver is the extension of the offer. The broker announced in May that it is launching a platform for private investors to participate in IPOs alongside huge Wall Street funds.

Prospects after the IPO

It is important to understand that the past year and the beginning of this year were extraordinary. Until now, Robinhood has devoted all its efforts to supporting growth in the United States, and the current very limited functionality of the site was enough. With the funds raised during the public offering, the broker will receive resources for the development of new products and services (adding new financial assets to the site, its own payment service, etc.), as well as expanding the geography. Now he only works in the USA. This can smooth out the transition period after explosive growth.

Among the favorable factors is the maturation of the core audience - millennials - which may be followed by an increase in investments.

Robinhood's reputation as a platform for speculative deals could limit this positive effect. Excessive attention from regulators also creates risks - they can introduce potential restrictions that complicate the work of a startup. In early July, Robinhood received a record $ 70 million fine from FINRA for harming millions of clients. FINRA investigated the actions of Robinhood and came to the conclusion that since the fall of 2016 the broker has incorrectly informed users about the possibility of entering into transactions with margin, about the number of funds on clients' accounts, their purchasing power, and the risk of losses in options. The company incorrectly reported negative account balances to some of its clients.

The attention of regulators can pose a threat to the entire business model, in which the main source of income is the payment of market makers for orders.

Also, do not forget that the competition in the brokerage market is growing. Large brokers not only reduce commissions but also consolidate. For example, Charles Schwab acquired TD Ameritrade, and Morgan Stanley bought the broker E-Trade. In addition, new, but already well-known players are entering the market.

And new players are not asleep: there are already projects that may press Robinhood in the future. For example, the Acorns application, where users do not make their own decisions about where to invest, but trust "artificial intelligence". The algorithm makes investment decisions based on user preferences. You don't need to spend a lot of time to figure out where to invest, the task is simplified even more, and this is what consumers are striving for.

[thereaderbooks]

{ PDF } Ebook Cracking the Coding Interview 189 Programming Questions and Solutions Free download [epub]$$

[PDF] Download Ebook | READ ONLINE Cracking the Coding Interview: 189 Programming Questions and Solutionsbody {font-family: Helvetica, Arial, sans-serif;}#example1 {border: 2px solid black;padding: 25px;background: lightblue;background-repeat: no-repeat;background-size: 100% 100%;}nav {margin:auto;text-align: left;width: 80%;font-family: roboto;}nav ul {list-style: none;position: relative;display: inline-table;width: 80%;}nav ul li{float:left;}nav ul li:hover{background:#FFFF00;}nav ul li:hover a{color:#000;}nav ul li a{display: block;padding: 25px;color: black;text-decoration: none;}p{position:absolute;top: 20px;z-index: 2;color: black;background-color:yellow;}{ PDF } Ebook Cracking the Coding Interview: 189 Programming Questions and Solutions Free download [epub]$$

Cracking the Coding Interview: 189 Programming Questions and Solutions

[PDF] Download Cracking the Coding Interview: 189 Programming Questions and Solutions Ebook | READ ONLINE

Author : Gayle Laakmann McDowell Publisher : Careercup ISBN : 0984782850 Publication Date : 2015-7-1 Language : eng Pages : 708

To Download or Read this book, click link below:

http://read.ebookcollection.space/?book=0984782850

[Doc]

Synopsis : { PDF } Ebook Cracking the Coding Interview: 189 Programming Questions and Solutions Free download [epub]$$

I am not a recruiter. I am a software engineer. And as such, I know what it's like to be asked to whip up brilliant algorithms on the spot and then write flawless code on a whiteboard. I've been through this as a candidate and as an interviewer.Cracking the Coding Interview, 6th Edition is here to help you through this process, teaching you what you need to know and enabling you to perform at your very best. I've coached and interviewed hundreds of software engineers. The result is this book.Learn how to uncover the hints and hidden details in a question, discover how to break down a problem into manageable chunks, develop techniques to unstick yourself when stuck, learn (or re-learn) core computer science concepts, and practice on 189 interview questions and solutions.These interview questions are real; they are not pulled out of computer science textbooks. They reflect what's truly being asked at the top companies, so that you can be as prepared as possible. WHAT'S INSIDE?• 189 programming interview questions, ranging from the basics to the trickiest algorithm problems.• A walk-through of how to derive each solution, so that you can learn how to get there yourself.• Hints on how to solve each of the 189 questions, just like what you would get in a real interview.• Five proven strategies to tackle algorithm questions, so that you can solve questions you haven't seen.• Extensive coverage of essential topics, such as big O time, data structures, and core algorithms.• A behind the scenes look at how top companies like Google and Facebook hire developers.• Techniques to prepare for and ace the soft side of the interview: behavioral questions.• For interviewers and companies: details on what makes a good interview question and hiring process.

[filepdfreader]

Ebooks download Dutton's Orthopaedic Examination  Evaluation and Intervention Free Online

"

[PDF] Download Ebook | READ ONLINE Dutton's Orthopaedic: Examination, Evaluation and Interventionbody {font-family: Helvetica, Arial, sans-serif;}#example1 {border: 2px solid black;padding: 25px;background: lightblue;background-repeat: no-repeat;background-size: 100% 100%;}nav {margin:auto;text-align: left;width: 80%;font-family: roboto;}nav ul {list-style: none;position: relative;display: inline-table;width: 80%;}nav ul li{float:left;}nav ul li:hover{background:#FFFF00;}nav ul li:hover a{color:#000;}nav ul li a{display: block;padding: 25px;color: black;text-decoration: none;}p{position:absolute;top: 20px;z-index: 2;color: black;background-color:yellow;}Ebooks download Dutton's Orthopaedic: Examination, Evaluation and Intervention Free Online

Dutton's Orthopaedic: Examination, Evaluation and Intervention

[PDF] Download Dutton's Orthopaedic: Examination, Evaluation and Intervention Ebook | READ ONLINE

Author : Mark Dutton Publisher : McGraw-Hill Education / Medical ISBN : 1260143872 Publication Date : 2019-11-7 Language : eng Pages : 1584

To Download or Read this book, click link below:

http://read.ebookcollection.space/?book=1260143872

{DOWNLOAD}

Synopsis : Ebooks download Dutton's Orthopaedic: Examination, Evaluation and Intervention Free Online

The #1 orthopaedic evidence-based textbook and reference guideA Doody's Core Title for 2020! Dutton's Orthopaedic: Examination, Evaluation and Intervention provides readers with a systematic logical approach to the examination and intervention of the orthopedic patient. This comprehensive and up-to-date fifth edition strikes the perfect balance in its coverage of the continuum of care of an orthopaedic patient. The content emphasizes the appropriate use of manual techniques and therapeutic exercise while outlining the correct applications of multiple adjuncts to the rehabilitative process.The content reflects the consistent unified voice of a single author-a prominent practicing therapist who delivers step-by-step guidance on the anatomy, biomechanics, examination, and treatment of each joint and region. This in-depth coverage leads you logically through the systems review and differential diagnosis aided by decision-making algorithms and features new coverage on balance, pain assessment, and concussions. New videos on testing and method techniques are available on AccessPT.This edition has an added 10-15 case studies as well as updated chapters to reflect the latest research and treatment techniques."

[ebookpdflibrary]

(Epub Download) Machine Learning For Absolute Beginners A Plain English Introduction (Download Ebook)

"

[PDF] Download Ebook | READ ONLINE Machine Learning For Absolute Beginners: A Plain English Introductionbody {font-family: Helvetica, Arial, sans-serif;}#example1 {border: 2px solid black;padding: 25px;background: lightblue;background-repeat: no-repeat;background-size: 100% 100%;}nav {margin:auto;text-align: left;width: 80%;font-family: roboto;}nav ul {list-style: none;position: relative;display: inline-table;width: 80%;}nav ul li{float:left;}nav ul li:hover{background:#FFFF00;}nav ul li:hover a{color:#000;}nav ul li a{display: block;padding: 25px;color: black;text-decoration: none;}p{position:absolute;top: 20px;z-index: 2;color: black;background-color:yellow;}(Epub Download) Machine Learning For Absolute Beginners: A Plain English Introduction (Download Ebook)

Machine Learning For Absolute Beginners: A Plain English Introduction

[PDF] Download Machine Learning For Absolute Beginners: A Plain English Introduction Ebook | READ ONLINE

Author : Oliver Theobald Publisher : Independently Published ISBN : 1549617214 Publication Date : 2018-1-1 Language : Pages : 164

To Download or Read this book, click link below:

http://happyreadingebook.club/?book=1549617214

[Epub]$$

Synopsis : (Epub Download) Machine Learning For Absolute Beginners: A Plain English Introduction (Download Ebook)

Featured by Tableau as the first of '7 Books About Machine Learning for Beginners' Ready to crank up a virtual server and smash through petabytes of data? Want to add 'Machine Learning' to your LinkedIn profile?Well, hold on there...Before you embark on your epic journey, there are some theory and statistical principles to weave through first.But rather than spend $30-$50 USD on a dense long textbook, you may want to read this book first. As a clear and concise alternative to a textbook, this book provides a practical and high-level introduction to machine learning. Machine Learning for Absolute Beginners Second Edition has been written and designed forabsolute beginners . This means plain-English explanations and no coding experience required. Where core algorithms are introduced, clear explanations and visual examples are added to make it easy and engaging to follow along at home.This major new edition features many topics not covered in the First Edition, including Cross Validation, Data Scrubbing and Ensemble Modeling. Please note that this book is not a sequel to the First Edition, but rather a restructured and revamped version of the First Edition. Readers of the First Edition should not feel compelled to purchase this Second Edition. Disclaimer:If you have passed the 'beginner' stage in your study of machine learning and are ready to tackle coding and deep learning, you would be well served with a long-format textbook. If, however, you are yet to reach that Lion King moment-as a fully grown Simba looking over the Pride Lands of Africa-then this is the book to gently hoist you up and offer you a clear lay of the land.In this step-by-step guide you will learn: - How to download free datasets- What tools and machine learning libraries you need- Data scrubbing techniques, including one-hot encoding, binning and dealing with missing data- Preparing data for analysis, including k-fold Validation- Regression analysis to create trend lines- Clustering, including k-Means Clustering to find new relationships- The basics of Neural Networks- Bias/Variance to improve your machine learning model- Decision Trees to decode classification- How to build your first Machine Learning Model to predict house values using PythonFrequently Asked QuestionsQ: Do I need programming experience to complete this book?A: This book is designed for absolute beginners, so no programming experience is required. However, two of the later chapters introduce Python to demonstrate an actual machine learning model, so you will see programming language used in this book. Q: I have already purchased the First Edition of this book, should I purchase this Second Edition?A: As majority of the topics from the First Edition are covered in the Second Edition, you may be better served reading a more advanced title on machine learning.Q: Can I get access to the Kindle version of this book?A: Yes. Under Amazon's Matchbook program, the purchaser of this book can add the Kindle version of this title (valued at $3.99 USD) to their Amazon Kindle library at no cost.Q: Does this book include everything I need to become a machine learning expert?A: This book is designed for readers taking their first steps in machine learning and further learning will be required beyond this book to master machine learning."

[kitwallace]

Miller indices to polyhedra

Using OpenSCAD CSG operations

A while back (well 6 years ago) , I got interested in computing gem cuts in OpenSCAD.  My approach then used the CSG operations to put facets on a sphere as in this post on diamond cuts. The specification of a gem facet uses spherical coordinates : azimuth,  polar angle and radial distance. These correspond to the settings on a faceting machine with which muliple facets around the z axis can be cut at even increments by stepping the azimuth for a fixed polar angle. 

This led to an interest in crystal forms and the use of Miller indices to define the form.  Individual faces are defined by the normal to the face and its distance from the origin. eg  110,1. My approach here to was to use CSG operations as in this post.  Crystal descriptions use a base indice and symmetry rules which depend on the crystal system, eg  {100} , 1 , cubic  to generate the set of simple face indices - here the 6 faces -  001,010,100,001,010,100  where 1  mean -1 [usually written as 1 with bar over] This worked well and allowed me to create some of the irregular polyhedral in the cubic system as well as crystal forms with descriptions taken from the Dexter programme by Mark Holtkamp .  

Computing vertices and faces

The CSG approach allows the solids to be constructed and printed, but I wanted to be able to produce other forms of the solids, such as the open-face form or a net of the solid.  These transformations require vertex and face data which is not available from the constructed OpenSCAD objects. The aim then was to transform a crystal’s description into vertex/face data computationally.  The full procedure involves a  number of steps:

1.  Expand the crystal description using the defined symmetry rules into a set of simple Miller indices.  This was addressed in the previous work using CSG to create the solids.  So far I have handled only cubic systems.

2   Face normals to vertices The algorithm for this is outlined by Eric Dowty , the developer of the impressive Shape software. Every combination of three faces is intersected,  ignoring those with parallel faces.  Any such vertex which is outside any of the faces, based on perpendicular distance to the face is ignored. Finally we remove duplicate vertices. 

3  Vertices to hull Initial OpenSCAD code for an incremental construction of the hull was provided by Alexander Pruss on Thingiverse which yields triangular faces.  

4  Merge coplanar triangular faces  This stitches together adjacent coplanar triangles to form a polygonal face.

5  Generate forms from the vertex/face descriptions.  Here I am able to use my existing OpenSCAD code to generate solid, wireframe and open-face forms as well as nets, and can also use the conway operations to further transform the resultant polyhedra.

Tolerance is needed on most numeric tests, such as coplanarity, vertex identity and sidedness.

By comparison, the conversion from the representation as vertices and faces to Miller indices is trivial, so the easy way to check that the procedure is working is to round-trip a known solid from polyhedron to Miller and then back to a polyhedron or vice-versa. The only restriction is that only convex solids can be so transformed.

Examples

The Gyroid  (pentagonal icositetrahedron)

The regular version is one of the catalan solids. The pentagonal face is irregular.  In crystallography, the shape has a Miller index of {3 2 1}  and gyroid symmetry, resulting in irregular pentagonal faces.

Openface form

Nets 

Irregular solids 

An advantage of the Miller representation of a solid is that the position of each face can be changed by altering its distance from the origin.  This corresponds to different growth rates on different faces of a crystal, but by Steno’s law,the    law of constancy of interfacial angles, leaves the mineral shape unchanged.  So a random pertubation of the face distances gives rise to a randomly varied solid. Here is a rhombic dodecahedron {110} 

with perturbated faces:

which are now a mixture of 4-,5 and 6-sided faces.

Text on Faces

With a vertice/face description, we can also place text on a face.  Here is a unfair die - made by adjusting the two xy-faces - there are better uses of labeling :)

The solid can also be oriented so it is placed on its largest face for printing.

Compound solids

Another feature of the Miller representation is that we can create compounds of solids by concatenating the lists of Miller indices for each component. So a combination of a cube and a tetrahedron is simple to construct and to vary by  changing the face distances.

One benefit is that a form can be cut in any plane by adding a single indice - for example to cut a crytstal form in half vertically for ease of printing we can add [[0,0,-1],0 ].

Quasi crystal

Physical crystals are a lattice of the same molecule so Miller indices of physical crystals are restricted to integer values.  However computationally we are not so restricted. Many of the regular solids can be created from Miller indices as the work of  Zefiro and Ardigo shows. For example, the regular dodecahedron can be represented as {1 phi 0 } where phi is the golden ratio:

Crystals

The forms of real mineral crystals can be repesented as compounds of a number of simpler forms.  This is one of the forms of Boracite from the Smorf database

and its net:

and this version of Zircon from AuntDaisy on Thinigiverse 

Last word

It’s been a while to get to this stage in the quest to generate crystal forms from Miller representations using only user-space computations in OpenSCAD.  Some code is available on GitHub .  There is still work to do, particulaly to handle crystal systems with non-orthogonal axes. 

I have been inspired and helped by many in the Thingiverse (now sadly only useful as an archive it seems ) and OpenSCAD communities, for which grateful thanks.  

[nbanalytics]

success

fail

Feb MAR Apr 23 2018 2019 2020

26 captures

21 Jan 2016 - 27 Sep 2019

About this capture

COLLECTED BY

Organization: Alexa Crawls

Starting in 1996, Alexa Internet has been donating their crawl data to the Internet Archive. Flowing in every day, these data are added to the Wayback Machine after an embargo period.

Collection: Alexa Crawls

Starting in 1996, Alexa Internet has been donating their crawl data to the Internet Archive. Flowing in every day, these data are added to the Wayback Machine after an embargo period.

TIMESTAMPS

__wm.bt(625,27,25,2,"web","http://nbanalytics.tumblr.com/","20190323161114",1996,"/_static/",["/_static/css/banner-styles.css?v=HyR5oymJ","/_static/css/iconochive.css?v=qtvMKcIJ"]); NBAnalyticsfigure{margin:0}.tmblr-iframe{position:absolute}.tmblr-iframe.hide{display:none}.tmblr-iframe--amp-cta-button{visibility:hidden;position:fixed;bottom:10px;left:50%;transform:translateX(-50%);z-index:100}.tmblr-iframe--amp-cta-button.tmblr-iframe--loaded{visibility:visible;animation:iframe-app-cta-transition .2s ease-out} /* If this option is selected, the theme will use a solid background instead of an image */ body { background: #000000 url(http://web.archive.org/web/20190323161114im_/http://static.tumblr.com/06e5dcbee1eebcb1fc08923a0dbbdf9e/deauzpq/9Mumzs7m4/tumblr_static_maxresdefault.jpg) fixed top left; } /* If this option is selected, the theme will use a solid background instead of an image */ var enableAudiostream = false; var audioplayerTagFilter = false; var enableDisqus = false; var enableTwitter = false; var enableFlickr = false; var enableInstagram = false; var totalBlogPages = '1'; {"@type":"ItemList","url":"http:\/\/web.archive.org\/web\/20190323161114\/http:\/\/nbanalytics.tumblr.com","itemListElement":[{"@type":"ListItem","position":1,"url":"http:\/\/web.archive.org\/web\/20190323161114\/http:\/\/nbanalytics.tumblr.com\/post\/75952859870\/ranking-the-nba-teams-with-a-genetic-ml-algorithm"},{"@type":"ListItem","position":2,"url":"http:\/\/web.archive.org\/web\/20190323161114\/http:\/\/nbanalytics.tumblr.com\/post\/74366758922\/what-team-benefits-the-most-from-home-cooking"}],"@context":"http:\/\/web.archive.org\/web\/20190323161114\/http:\/\/schema.org"}

Now Playing Tracks

NBAnalytics

Facebook

Twitter

Google

Tumblr

Ranking the NBA Teams with a Genetic ML Algorithm

Which team is the best in the NBA? A question that most of us basketball fans think we know the answer to yet often we find it so hard to come to a consensus. In the ever-popular world of basketball analytics, I would argue that mathematical team rankings are probably the most popular and contentious problem that people try to “solve”.  About two years ago I attacked this topic of debate in my very first foray into the world of basketball analytics. I was naive and inexperienced at the time, but my eventual failure led me to continue to explore the world of basketball data, statistics and machine learning…

From a math point of view there are lots of ways to approach the problem developing a computer ranking system. I will begin by establishing that the goal of any NBA ranking system should be to predict playoff success. If two teams are paired together in a playoff bracket, the higher ranked team should win more often.  Additionally, the larger the difference in rating scores, the more likely the favorite team should win the playoff series. Here are a couple of simple models one might use to predict playoff success. I will use these as baseline models to which I compare my own ranking system.

The most basic way to measure team quality from the regular season is winning percentage.  Below we see a plot of playoff wins versus regular season winning percentage.

There is definitely a positive and statistically significant correlation of  0.571, but can we do better? The percent of the variance in playoff success explained by regular season success alone is only 33%. Not to mention that half of the NBA champion teams fall outside of the 95% confidence interval for prediction.  Obviously there are other factors that should be taken into account when predicting postseason success.

Another way to measure team quality and a popular one with computational ranking systems is average margin of victory.  Below is a plot of the average margin of victory versus playoff wins.

This metric also has a positive correlation with playoff success with a statistically significant value of 0.599, which is slightly better than using regular season wins to predict playoff wins.  The percent of the variance explained is also slightly better for margin of victory at 36%.  However, this model also fails to include many of the champions in the 95% confidence band.

So how can be expand our ranking system to better predict postseason success? Similar to my take on measuring home court advantage, I believe that any ranking system needs to take into account the various strengths of the opponents that each teams play as well as the quality of performance in each of those games relative to an average team would against the same opponents.

From this simple criteria I developed 10 performance measures that could be included in the ranking of every team in two different categories for every game they play:

Strength of opponent

Total opponent winning percentage at time of the game

Opponent winning percentage at site of game (home/away) at time of the game

Opponent’s avg. margin of victory

Opponent’s avg. margin of victory at site of game (home/away)

Opponent’s winning percentage in last X games

Quality of play in each game compared to expected performance

Margin of victory

Over/under opponent’s points against avg.

Over/under opponent’s points for avg.

Over/under opponent’s points against avg. at site (home/away)

Over/under opponent’s points for avg. at site (home/away)

I added a few other factors to consider in the ranking algorithm as well. Overall winning percentage was included because it is a standard baseline for team rankings. Additionally, the opponent’s recent level of play could be factored into the strength of the opponent, as well a discount factor for how long ago games were played.

From these factors I created a linear function to combine the Strength of Opponent factors and Quality of Play factors with coefficients.

These two larger factors are then linearly combined with how recent the game was to the current point in time and the overall team winning percentage, again, with coefficients.

For a final team ranking, the score of every game is summed and the teams ordered from highest to lowest.

The value of each of these factors and how I combined them is debatable.  Any ranking system is going to have some inherent subjectivity and assumptions based on the system designer and the data feed into it. The reason that I support this model is not because of the factors it takes into account, but rather that the factors can be combined in an infinite number of ways in an effort to fit the model to historical results.  The theory behind the model is that the coefficients will shed light into what actually matters in winning basketball games.  If defense is more important than offense the the coefficient X with be fit to be larger than the coefficient W.  If performance on the road or performance at home matters, then the site specific coefficients with be large and they will be close to zero if site-specific performance is irrelevant. 

This raises the question of how to best train the coefficients on historical data.  At the time that I did this study, I had zero training in machine learning, so I hacked together an algorithm of my own creation that would generate random starting coefficients and search through the infinitely sized set of coefficients looking for the most predictive set.  I was inspired by nature’s own machine learning technique and used breeding, mutation and natural selection to move through the coefficient search space. 

The steps of the genetic algorithm were as follows:

I populated a number of “parent” sets of coefficients.  I used my basketball knowledge to create coefficients I assumed would be near the optimal values for some of the parents, but randomly generated others so that my population would attack the problem from multiple “perspectives” as my intuition is not necessary what is best.

The parent sets were then “breed” with each other, two at a time, to create a large population of “children.” Each child received half of the coefficients from two different parents.

Each coefficient for every child was given the opportunity to “mutate” into a value other than that of the child’s parents.

Each child set of coefficients was then used to calculate the end of season ranking for every playoff team during the 2002-2003 through 2011-2012 NBA seasons.  These rankings were used to see if the children accurately predicted the winner of each of the 150 different playoff series that occurred during those ten seasons with extra weight given to predicting the eventual champion. 

The top 10 most predictive children sets were “naturally selected” to be the parent sets for the next “generation” of the algorithm.

The algorithm stopped when it accurately predicts all 10 NBA champions or reaches a pre-specified maximum number of generations.

After creating the algorithm I sat back and let it run for a while to see what kind of results would pop out. It was good to see that my “expertly” chosen coefficients accurately predicted the result of most playoff series but the algorithm quickly found a better combination.  In general, the the algorithm asymptotes very quickly just above 70% prediction accuracy for all playoff series.  However after just a few generations, it struggles to improve itself and never seems to predict more than 4 out of the 10 championship teams before the start of the playoffs, but it does predict 8 out of the 10 winners given the Finals match-up.  

More importantly it appears that the set of coefficients that produce relatively high accuracy has many local maxima, as very different sets of coefficients produce very similar accuracy results. It was interesting to see these various formulas that my genetic algorithm converged on.  Perhaps this sheds some light into being able to forecast post-season success. Either some playoff series are easy to predict (this makes sense for first round match-ups, but not for later rounds) or there are many ways to create quality teams. To avoid getting stuck at the first local maxima encountered, the algorithm allows for every child to have a random mutation that differs from either of the parents.  Just as in nature this allows for innovation and diversification of the population.  Along these same lines, one of the keys for arriving at the best model in light of many local maxima is to have a suitably large population to breed from. The more parents in the population, the more diverse the population, and the more opportunity the algorithm has of finding the true most-predictive model. 

I investigated the impact of having a larger population, in spite of the extra computation time, by increasing the parent population size and the number of children produced each generation. As an example, here is a plot of the progression of the model over each generation with a population of 100, rather than the 10 shown above.

The variance in the population of models accuracy increases any time the population size is increased.  It also takes more generations for the population to converge toward a homogeneous level of accuracy. More importantly, changing the population size does not increase the models ability to converge to a global optima as the total accuracy does not change much for any population size of at least 10. It was disappointing that the model very quickly reaches its most optimum set of coefficients regardless of the model parameters. 

I after investigating the effect of changing the population and it’s effect on convergence, I ran the model one last time and the genetic algorithm found the most predictive model. Here is the final rankings of the model compared to the baseline models’ rankings for the 2012-2013 season.

Overall the rankings of all three are pretty similar. This is not too surprising given that my model is linear combinations of values that are for the most part derived from winning percentage and margin of victory.  The teams with the largest changes in my ranking from the baseline rankings are either teams that were doing much better or much worse in their most recent games. So this is how the teams fall into order during regular season, but does it translate into playoff prediction?

Here are the predictions for the 2013 NBA playoffs for he three models along side what actually went down….

In this particular season, my model is no better than the simple predictive models based on regular season wins and regular season margin of victory.  Only the wins model was able to predict the champion by ranking Miami first before the start of the playoffs.  However, the goal is not to have the highest accuracy in a single season but have the model generalize to be the most predictive in any future season.  Here is how the my ranking model predicts the results over the ten seasons to which the model was fit. The assumption of a linear relationship was used just as with the baseline models earlier.

My ranking system scales each team’s score to fall between 0 and 100 where the 30th ranked team has a score of 0 and the top ranked team a score of 100. As expected this team score is positively correlated with playoff success with a statistically significant value of 0.525. This is unfortunately worse than the baseline models despite being the model that the genetic algorithm found to be most predictive of postseason success. The percent of the variance explained is also worse at only 28%.  But, it turns out that the team’s score it not the best metric from my ranking system for predicting playoff success because team scores are scaled based on the teams’ stats for that season.  So scores can not  be accurately compared with one another across seasons, and it is more realistic to predict playoff success based on the teams’ rank for that season.

This performs better, as expected, but it is still worse than the baseline models of regular season wins and regular season margin of victory. The correlation is only 0.553 and the percent of variance explained only 31%. 

In light of these results, there are certainly areas where this model could  be improved. Because of computation time, many of the algorithm iterations were done with too small a population and converged on local optima too soon. I did not play with any of the parameters around the randomization of the coefficients to mutate or how the parents that were “mated” were chosen.  I suspect that there are ways to create population clusters or engineer other algorithm features to make the genetic algorithm converge on the best optima quicker.  However, the real problem with the model has to do with the choice of a genetic algorithm to begin with.

If I were to re-do this analysis with my skill set today, I would use a different method to optimize the linear model coefficients.  Ordinary least squares optimization would converge more quickly to the best-fit coefficient values, but it unclear how to set up the data set to accommodate this method and a squared error penalization may not be the best assumption in this situation.  Another option would be to use an expectation maximization algorithm to converge the parameters to the best fit values from my initial assumption values.  This would be an interesting experiment and is more similar to my original concept. Of course, something more powerful such as Random Forests or Neural Networks could prove more accurate with enough input information, but these methods are not for fitting parameters to an assumed model structure, but rather black-box model generators that sacrifice model interpretability. My choice of a genetic algorithm was driven by personal curiosity, and as a novice in machine learning I was unaware of what tool would be best suited to the task. 

One last way to improve model would be to include more information such as, number of days rest, injuries and how types of teams match-up with one another.  

In conclusion, it seems noble in the scientific sense to try and put a formula of the results of the NBA playoffs and be able to measure the quality of a basketball team, but the truth is really the old cliché, basketball games and trophies aren’t won on paper, but rather, on the hardwood.  I learned a few analytics lessons. More complex models are not guaranteed be better than the simpler models they hope to improve upon, and any data scientist needs to know when to use the right model for the given problem. While I never expected a genetic algorithm to be the best way to fit my model, it turns out that it was never properly suited to the task given my evaluation measure and the computation time involved.

As fan of the sport I have come to realize that this is actually an encouraging result.  It should not be easy to change conventional wisdom or predict the future. I am glad that there is the white noise randomness of blown charging calls and streak-shooting that make each game dramatic and exciting. Sure there are better measures of the true quality of a team beyond winning percentage or margin of victory, but if we knew with any certainty the outcome of a basketball, why would we even bother to watch?

This analysis was done in Matlab and the results processed in a combination of Matlab and R.

All of the data was courtesy of basketball-reference.com 

More general information about genetic algorithms can be found at http://en.wikipedia.org/wiki/Genetic_algorithm

Other computer ranking systems for NBA teams can be found at:

http://www.usatoday.com/sports/nba/sagarin/

http://www.teamrankings.com/nba/ranking/overall-power-ranking-by-team

http://espn.go.com/nba/hollinger/powerrankings

Feb 7

Facebook

Twitter

Google

Tumblr

What team benefits the most from home cooking?

Basketball just like any spectator sport is subject the phenomenon we all know and love as “Home Court Advantage.” Even the casual sports fan knows that their favorite team has a better chance of winning in their home arena than they do in somebody else’s. In the NBA, the rule of thumb is that the home team tends to do about 3 points better than they would if the game were played at a neutral site.  That means that there is a whopping 6 point swing depending on whose gym the game is being played in which is significant considering that the average margin of victory in the NBA is only 3.3 points.  

So what is the cause of this crowd pleasing phenomenon?  The standard theories include: the home crowd support, player’s sleeping in their own bed, the home game routine, and the additional rest home teams enjoy courtesy of the typical NBA season (see endnote references). I’m sure in reality that it is some combination of all of these factors, but who’s to say that all home court advantages were created equal?

Awhile ago, I spent a day investigating this very topic because the best home court advantage in the NBA is a pretty frequent subject in national TV telecasts.  The media and coaches love to point to how are it is to win in places like the Pepsi Center in the mile-high altitude of Denver or beneath the raucous crowds at Oracle Arena in Oakland.  So do the numbers back up these usual candidates for toughest places to play in the NBA?  First, a clear definition of home court advantage needs to be established.

I care about consistent fan bases and a home court advantage that is independent of individual players or particular team rosters in a given year, so it is important to study the impact of home court advantage over a number of seasons. I chose to study all NBA games from the 2002-2003 season through the 2011-2012 season, a period of time that is long enough for NBA rosters to have completely turned over during that time frame and for most to have had both good and bad years. Also, calculating a team’s benefit from playing at home should be more sophisticated than simply subtracting each teams away margin of victory from their home margin of victory. This simple metric does not take into account the different schedules that each team plays or the imbalance in the number home vs. away games that teams play against each other (see endnote references).  A team like the Houston Rockets that have 26 homes against the stronger eastern conference whereas the Toronto Raptors have only 15 home games against Western conference foes. This season at least, the Raptors play one game home and one road game against the Rockets compared to the the much weaker Orlando Magic against whom they play two home games and only one away game.  Toronto’s home margin would be expect to be ballooned slightly by having an easier home schedule than road schedule since the other road game is most likely against a team of higher quality that the Magic.

Therefore, I attempted to insulate my calculation of home court advantage against the different schedules that every team experiences and the differences in schedules across NBA seasons.  This is done by calculating the average points for and against for all visiting teams and then comparing that to how that team does in all of the the 30 NBA arenas.  The strength of a home court advantage is based on how many more points the home team tends to win by against its opponents compared to how many points the visiting teams tend to lose by.  This normalizes the home margin of victory against the strength of the visiting opponents for all teams. This value can then be compared to how well the same team does on the road to create the average benefit that each team gets from playing at home.

In essence, the best home court advantage does not belong to the team that wins the highest percentage of their home games (That was San Antonio at 72% during the 10 seasons of study). Nor is it the team that has the largest increase in home winning percentage over road winning percentage (That was Washington with over a 40% increase). It is the team whose expected point differential for home games performance increases the most in expected point differential between home games and away games relative to the average point differential of the opposing team.

As an example.  Let’s study the games between Houston and Toronto from the 2012-2013 season.  Houston averaged 106.0 points per game and allows 102.5 points per game for a average margin of victory of 3.5 points.  Toronto averaged 97.2 points per game and allows 98.7 points per game for an average margin of victory of -1.5 points. In the first game, in Houston, the Rockets won 117-101.  Toronto prevailed at home in the rematch 103-96. Assuming both of the games had been at a neutral site,we would have expected Houston to win both games by about 2.5 points (given that both teams had played teams of equal quality of course). To calculate the advantage of home court between Toronto and Houston I looked at the change in the expect value for margin of victory. Houston increased their expected margin from 2.5 to 16 for an increase of 13.5 points at home.  The road margin dropped from the 2.5 expected to -7 for a -9.5 points.  In this match up, home court was worth a whopping 23 points to the Houston Rockets and, via symmetry, to Toronto as well. I performed this calculation for all of the 29 head-to-head matched between teams for each season and then averaged the increases to find an average increase in margin of victory for each team over the whole season.  To reduce the variation that is expected from season to season, I then average then ten seasons of study to create an estimate for the standard home court advantage expected in all 30 NBA arenas. 

So now for the results of the study which is what we all want to see…

Below is a ranked chart of each team with the changes in Winning Percentage, Points For, Points Against, and Margin of Victory between home and away from the 2002-2003 to 2011-2012 seasons.

Unsurprisingly, the usual suspects rise to the top.  However notice that often forgotten Utah gains the most from playing at home. I suspect this is for having an elevation only 1,000 feet lower than Denver and better than average crowd that loves their only major pro-sports team in town.

As I claim that my analyses are grounded in math and science, I must ask whether these results are statistically significant.  First let’s look at a plot of the three best and three worst teams’ home advantage over the ten seasons compare to the average home court advantage that year. 

While I admit that there is a lot of noise from season to season, there is a clear difference between Utah, Denver, and Golden State compared to Minnesota, Philadelphia and Boston.  The former teams almost always have above average home court advantages while the latter teams almost always under perform at home.

But are these claims statistically significant? Boston’s league worst home court advantage of 4.67 is statisitically different from the assumption that  home court advantage does not exist with a p-value of 2.1x10-9, a really small number.  So, I conclude that home court advantage does indeed exist, as well all expected. I then looked to see whether Boston’s and Utah’s advantages were statistically different than the league average. The resulting p-values were 0.004 and 0.001 respectively, so yes Utah can be considered a more difficult environment to play in compared to Boston, given the quality of the teams are the same. But the question we all care about is: Can we definitely say that Utah has the greatest home court advantage in the NBA? Namely, is the Jazz’s league lead 9.3 point advantage better than Denver’s 8.8 point advantage?

Well, we can not really make such a claim, as the p-value for the hypothesis test to whether Utah’s average home court advantage is greater than Denver’s is a rather large 0.37. In fact, I had to go all the way down to Sacramento with the sixth best advantage to be able to even claim that Utah has a significant advantage over the King’s with even a 90% confidence level.  Essentially, all of the usual suspects can make an argument that they place is the toughest to play, and there is no clear cut winner. In reality, it probably varies year to year based on the players on the roster and other factors like rest and injuries.

In conclusion, the effect of home court advantage is real. There is a clear difference in the effect of home court across the NBA as Utah’s advantage is twice that of Boston’s. However because there is a lot of variation in relative home court advantage from season to season there is no clear “hardest place to play” in the NBA.  Much of the effect of home court advantage can be clouded by the unbalanced strength of schedule in the NBA, but this can be accounted for by factoring in the opponent’s strength.  It is also unclear what individual variables contribute to this phenomenon but it appears that crowd support and altitude have an effect.

I also want to point out further points of research that could be done with this data include: investigating the relationship between team record and home court advantage or whether these variables are independent, why some teams advantage is primarily on offense or defense, why the increase in winning percentage is only loosely correlated to increase in margin of victory, and investigating if home court advantage is consistently around 3.2 every year or has an identifiable trend.  

This analysis was done in Matlab and the results processed in R.

All of the data was courtesy of basketball-reference.com

Below are a few links to related material:

Days Rest’s effect on Home Court Advantage-

http://www.amstat.org/chapters/boston/nessis07/presentation_material/Dylan_Small.pdf

How the NBA creates it’s schedule and the imbalances-

http://www.nbastuffer.com/component/option,com_glossary/Itemid,90/catid,44/func,view/term,How%20the%20NBA%20Schedule%20is%20Made/

Jan 23

1

Random post

Browse the Archive

Get the RSS

About

What started out at a hobby trying to separate basketball facts from opinion has led me to a career in data analytics. Perhaps I should share some of my mathematical musings...

Ask me anything

Connect

Linkedin

tumblrNotesInserted = function(notes_html) { $('.notes .note:not(.processed) img').each(function(i){ var note = $(this).parent().parent(); var avaurl = $(this).attr("src"); avaurl = avaurl.replace('16.gif','64.gif'); avaurl = avaurl.replace('16.png','64.png'); avaurl = avaurl.replace('16.jpg','64.jpg'); $(this).attr('src', avaurl).parent().addClass('avatar-wrap'); note.append($('<span class="ir note-glyph">')).addClass('processed'); }); $('.more_notes_link').prepend($('<div>',{'class':'more-notes-icon'})); } var _gaq=[['_setAccount','UA-43477248-2'],['_trackPageview']]; (function(d,t){var g=d.createElement(t),s=d.getElementsByTagName(t)[0]; g.src=('https:'==location.protocol?'//web.archive.org/web/20190323161114/http://ssl':'//web.archive.org/web/20190323161114/http://www')+'.google-analytics.com/ga.js'; s.parentNode.insertBefore(g,s)}(document,'script')); var themeTitle = "Fluid Neue Theme"; var url = "http://web.archive.org/web/20190323161114/http://fluid-theme.pixelunion.net"; (function() { var pxu = document.createElement('script'); pxu.type = 'text/javascript'; pxu.async = true; pxu.src = 'http://web.archive.org/web/20190323161114/http://cdn.pixelunion.net/customize/pxucm.js'; var isCustomize = (window.location.href.indexOf('/customize_preview_receiver.html') >= 0) ? true: false; var isDemo = (window.location.href.indexOf(url) >= 0) ? true: false; (isCustomize || isDemo) && ((document.getElementsByTagName('head')[0] || document.getElementsByTagName('body')[0]).appendChild(pxu)); })(); var pxuConversionLabel = "ex5HCJmipgIQ58Wg4gM"; var pxuDemoURL = "fluid-theme.pixelunion.net"; var pxuIsDemo = (window.location.href.indexOf(pxuDemoURL) != -1); var pxuTriggerConversion = (document.referrer.indexOf(pxuConversionLabel) != -1); if (pxuTriggerConversion && !pxuIsDemo) { /* <![CDATA[ */ var google_conversion_id = 1011360487; var google_conversion_language = "en"; var google_conversion_format = "3"; var google_conversion_color = "ffffff"; var google_conversion_label = pxuConversionLabel; var google_conversion_value = 40; /* ]]> */ }

(function(){ var analytics_frame = document.getElementById('ga_target'); var analytics_iframe_loaded; var user_logged_in; var blog_is_nsfw = 'No'; var addthis_enabled = false; var eventMethod = window.addEventListener ? "addEventListener" : "attachEvent"; var eventer = window[eventMethod]; var messageEvent = eventMethod == "attachEvent" ? "onmessage" : "message"; eventer(messageEvent,function(e) { var message = (e.data && e.data.split) ? e.data.split(';') : ''; switch (message[0]) { case 'analytics_iframe_loaded': analytics_iframe_loaded = true; postCSMessage(); postGAMessage(); postATMessage(); postRapidMessage(); break; case 'user_logged_in': user_logged_in = message[1]; postGAMessage(); postATMessage(); break; } }, false); analytics_frame.src = "http://web.archive.org/web/20190323161114/https://assets.tumblr.com/analytics.html?dfab06320413a6a34dbca419c4c70f2c#" + "http://web.archive.org/web/20190323161114/http://nbanalytics.tumblr.com"; function postGAMessage() { if (analytics_iframe_loaded && user_logged_in) { var is_ajax = false; analytics_frame.contentWindow.postMessage(['tick_google_analytics', is_ajax, user_logged_in, blog_is_nsfw, '/?route=%2F'].join(';'), analytics_frame.src.split('/analytics.html')[0]); } } function postCSMessage() { COMSCORE = true; analytics_frame.contentWindow.postMessage('enable_comscore;' + window.location, analytics_frame.src.split('/analytics.html')[0]); } function postATMessage() { if (addthis_enabled && analytics_iframe_loaded) { analytics_frame.contentWindow.postMessage('enable_addthis', analytics_frame.src.split('/analytics.html')[0]); } } function postRapidMessage() { if (analytics_iframe_loaded) { var is_ajax = ''; var route = '/'; var tumblelog_id = 't:XtTapjYtMmgXGemxL-VsnQ'; var yahoo_space_id = '1197719229'; var rapid_client_only = '1'; var apv = '1'; var rapid_ex = ''; analytics_frame.contentWindow.postMessage( [ 'tick_rapid', is_ajax, route, user_logged_in, tumblelog_id, yahoo_space_id, rapid_client_only, apv, rapid_ex ].join(';'), analytics_frame.src.split('/analytics.html')[0] ); } } })(); !function(s){s.src='http://web.archive.org/web/20190323161114/https://px.srvcs.tumblr.com/impixu?T=1553357474&J=eyJ0eXBlIjoidXJsIiwidXJsIjoiaHR0cDovL25iYW5hbHl0aWNzLnR1bWJsci5jb20vIiwicmVxdHlwZSI6MCwicm91dGUiOiIvIn0=&U=MNAPGBOLOM&K=5b3670896fe7836d54aac5bc1d96f7ffd6748f245e27eae2e1c41110d05db005&R='.replace(/&R=[^&$]*/,'').concat('&R='+escape(document.referrer)).slice(0,2000).replace(/%.?.?$/,'');}(new Image());

(function (w,d) { 'use strict'; var l = function(el, type, listener, useCapture) { el.addEventListener ? el.addEventListener(type, listener, !!useCapture) : el.attachEvent && el.attachEvent('on' + type, listener, !!useCapture); }; var a = function () { if (d.getElementById('tumblr-cdx')) { return; } var s = d.createElement('script'); var el = d.getElementsByTagName('script')[0]; s.async = true; s.src = 'http://web.archive.org/web/20190323161114/http://assets.tumblr.com/assets/scripts/vendor/cedexis/1-13960-radar10.min.js?_v=8d32508b0a251bebecb4853c987c5015'; s.type = 'text/javascript'; s.id = 'tumblr-cdx'; d.body.appendChild(s); }; l(w,'load',a); }(window, document)); !function(s){s.src='http://web.archive.org/web/20190323161114/https://px.srvcs.tumblr.com/impixu?T=1553357474&J=eyJ0eXBlIjoicG9zdCIsInVybCI6Imh0dHA6Ly9uYmFuYWx5dGljcy50dW1ibHIuY29tLyIsInJlcXR5cGUiOjAsInJvdXRlIjoiLyIsInBvc3RzIjpbeyJwb3N0aWQiOiI3NTk1Mjg1OTg3MCIsImJsb2dpZCI6IjE2NzQzMDY0NiIsInNvdXJjZSI6MzN9LHsicG9zdGlkIjoiNzQzNjY3NTg5MjIiLCJibG9naWQiOiIxNjc0MzA2NDYiLCJzb3VyY2UiOjMzfV19&U=FAHMBNNFHH&K=c8c29950492c11442d56bbbc69d51452c56935b7e4a6538331f6d3c3f6b3ed2a&R='.replace(/&R=[^&$]*/,'').concat('&R='+escape(document.referrer)).slice(0,2000).replace(/%.?.?$/,'');}(new Image());

[rnomics]

Long non-coding #RNA Hotair promotes gastric #cancer progression via miR-217-GPC5 axis.

Related Articles Long non-coding #RNA Hotair promotes gastric #cancer progression via miR-217-GPC5 axis. Life Sci. 2019 Jan 15;217:271-282 Authors: Dong X, He X, Guan A, Huang W, Jia H, Huang Y, Chen S, Zhang Z, Gao J, Wang H Abstract AIMS: The oncogenic role of l#ncRNA Hotair has been acknowledged in subset of malignancies, including gastric #cancer (GC). However, the detailed molecular mechanisms that contribute to its oncogenic role of are largely elusive. This study was designed to explore the underlying mechanism that contributes the regulatory role of Hotair in GC pathogenesis and progression. MAIN METHODS: Expression pattern of l#ncRNAs in GC tissues and adjacent normal tissues were identified by using microarray analysis. The cell proliferation of GC cells was examined by CCK-8 assay and colony formation assay, while migration and invasion capabilities of GC cells were examined by Transwell (with or without Matrigel) assay. Cell apoptosis was examined by Flow cytometer. qRT-PCR and western blotting were used to examine the expression of Hotair, miR-217, and other related genes. The potential target relationships were predicted by miRcode algorithm, and validated by dual luciferase reporter gene assay. KEY FINDINGS: We observed that Hotair was frequently up-regulated in GC tissues and cell lines, and high Hotair level was positively correlated with poor prognosis in GC patients. Knockdown of Hotair inhibited GC cells' viability, migration, invasion, Epithelial mesenchymal transition process. MiR-217 was decreased while GCP5 was increased in GC cells. Hotair negatively regulated the expression of miR-217 in GC while miR-217 targeted GCP5 to down-regulate its expression. Hotair promoted GC development by promoting GCP5 expression via sponging miR-217. SIGNIFICANCE: Hotair could serve as a potentially prognostic indicator and provide new light into its underlying biological-molecular mechanism in GC. PMID: 30557546 [PubMed - indexed for MEDLINE] http://bit.ly/2H5O9ze

[cophoenixseo]

How to Hire a Search Optimization Expert in Phoenix

No matter the service you provide, all businesses can benefit from having more customers, which begins with free traffic from Google.

Our Search Optimization Service is your unfair advantage in the Phoenix Arizona area.  

As a local business owner in Phoenix Arizona we know that you are seeking every advantage possible over your competition in the city. Never before has there been more competition for the merchandise or services that you sell. Watch this video to learn what search engine optimization can do to increase your online presence in the local market you serve.  

  When considering how to drive more traffic to a business website, a common assumption is that paid advertising is the easiest. However, it turns out the return on investment from search engine optimization is much stronger than PPC.   This video explains SEO versus pay per click.  

 Google’s study uncovered that buyer preference is nearly always for customized ads based on Phoenix Arizona. 67% of mobile users revealed a strong preference for SERPs presented by City like Phoenix, State such as Arizona, and ZIP code.

 We used this very approach to customize this page using the geography of the search area for a search engine optimization expert. Now think about this, how many seo firms can rank in hundreds of markets in the United States? Many cannot even demonstrate rankings in their own home town. SEO Ranker Agency is an expert SEO in Phoenix AZ. Visit seorankeragency.com to learn how we can impact your business with more leads and customers.

 Google’s online search engine utilizes a wide range of techniques to figure out which pages are presented on the first page of the outcomes. Their specific algorithm is a carefully kept secret. Still, there are a few basics to boost your online presence in the major search platforms such as Yahoo!, Bing, and Google search result pages. The term for this is search engine optimization, or SEO; other references to this service type is also online search optimization.

 If you think about the role of search engines, it is vitally important that their results are lacking any black hat techniques. This is why there are no guarantees as well as no fast systems for your site to rank. If an agency promises you a prime outcome, it’s most likely a fraud, or that they will apply optimization approaches that could lead to your website negatively hit by Google, and your hard work lost. Grab your free search engine optimization analysis to see what is needed for your site to beat the competition in your city and market. 

 Get found now to explode your business with more leads and customers! /* Toogle */ .icp_form-4-1 { /* Background Color */ background-color:#ecf0f1; /*background-color: #2980b9;*/ /*background-color:#e74c3c;*/ /*background-color:#f1c40f;*/ /*#2980b9,*/ /* Font Style */ font-family: 'Titillium Web', sans-serif, Arial; line-height: 1.5px !important; /*font-family: 'Maven Pro', sans-serif;*/ /*font-family: 'Roboto Condensed', sans-serif;*/ /*font-family:'Bitter', serif;*/ } .icp_form-4-1 img { max-width:100%; box-shadow:none; display: inline-block; } /* =================================================== */ /* Form 4 */ .icp_form-4-1 { /* Size and position */ width: 88%; margin: 0 auto 0px; padding: 4%; position: relative; /* Font styles */ /*color: #2c3e50;*/ vertical-align: top; text-align: center; font-family: 'Titillium Web', sans-serif, Arial !important; } .icp_form-4-1 .top4 { background: #2C3E50; margin-bottom:0px; width:110%; z-index:2; margin-left: -5%; padding: 8px 0% 5px 0%; } .icp_form-4-1 p { margin: 1% 0 1% !important; font-size: 14px !important; line-height: 1.0em !important; color: #141414 !important; text-align: center; font-family: 'Titillium Web', sans-serif, Arial !important; } .icp_form-4-1 h1 { font-size: 24px; padding-bottom: 0px; margin: 0 0 2% !important; line-height: 1em !important; font-weight: 700 !important; color: #141414 !important; font-family: 'Titillium Web', sans-serif, Arial !important; } .icp_form-4-1 h1:before { content: none; } .icp_form-4-1 h2 { font-size: 18px; padding-bottom: 10px; font-weight: 400; line-height: 1em; } .icp_form-4-1 input[type=text] { /* Size and position */ width: 80% !important; max-width: 80% !important; height: 37px !important; max-height: 37px !important; padding: 8px 3% 8px 3% !important; margin: 4% 0 0; margin-bottom: 15px; display: inline-block; /* Styles */ border: 0px solid #2C3E50; /* Fallback */ border: 0px solid rgba(78,48,67, 0.8); background: rgba(255,255,255,1); border-radius: 2px; box-shadow: 0 1px 0 rgba(255,255,255,0.2), inset 0 1px 1px rgba(0,0,0,0.1); -webkit-transition: all 0.3s ease-out; -moz-transition: all 0.3s ease-out; -ms-transition: all 0.3s ease-out; -o-transition: all 0.3s ease-out; transition: all 0.3s ease-out; /* Font styles */ color: #2C3E50; font-size: 13px; font-family: 'Titillium Web', sans-serif, Arial !important; } .icp_form-4-1 .icp_url { /* Size and position */ width: 80% !important; max-width: 80% !important; height: 37px !important; max-height: 37px !important; padding: 8px 3% 8px 3% !important; margin: 4% 0 0; margin-bottom: 15px; display: inline-block; /* Styles */ border: 0px solid #2C3E50; /* Fallback */ border: 0px solid rgba(78,48,67, 0.8); background: rgba(255,255,255,1); border-radius: 2px; box-shadow: 0 1px 0 rgba(255,255,255,0.2), inset 0 1px 1px rgba(0,0,0,0.1); -webkit-transition: all 0.3s ease-out; -moz-transition: all 0.3s ease-out; -ms-transition: all 0.3s ease-out; -o-transition: all 0.3s ease-out; transition: all 0.3s ease-out; /* Font styles */ color: #2C3E50; font-size: 13px; font-family: 'Titillium Web', sans-serif, Arial !important; } /* input[placeholder], [placeholder], *[placeholder] { color: white !important; } */ .icp_form-4-1 input::-webkit-input-placeholder { color: rgba(37,21,26,0.5); text-shadow: 0 1px 0 rgba(255,255,255,0.15); } /* WebKit and Blink (Safari, Google Chrome, Opera 15+) */ .icp_form-4-1 input:-moz-placeholder { color: rgba(37,21,26,0.5); text-shadow: 0 1px 0 rgba(255,255,255,0.15); } /* Mozilla Firefox 4 to 18 */ .icp_form-4-1 input:-ms-input-placeholder { color: rgba(37,21,26,0.5); text-shadow: 0 1px 0 rgba(255,255,255,0.15); } /* Internet Explorer 10 */ .icp_form-4-1 input[type=text]:hover { border-color: #2C3E50; } .icp_form-4-1 input[type=text]:focus, .icp_form-4-1 input[type=submit]:focus { box-shadow: 0 1px 0 rgba(255,255,255,0.2), inset 0 100px 1px rgba(0,0,0,0.1), 0 0 0 3px rgba(255,255,255,0.15); outline: none; } /* Fallback */ .no-boxshadow .icp_form-4-1 input[type=text]:focus { outline: 1px solid white; } .icp_form-4-1 input[type=submit] { /* Size and position */ width: 80% !important; max-width: 80% !important; height: 37px !important; max-height: 37px !important; padding: 8px 0% 8px 0% !important; /* Styles */ background: #1e73be !important; border-radius: 2px; border: 1px solid #a5a5a5 !important; cursor: pointer; -webkit-transition: all 0.3s ease-out; -moz-transition: all 0.3s ease-out; -ms-transition: all 0.3s ease-out; -o-transition: all 0.3s ease-out; transition: all 0.3s ease-out; /* Font styles */ color: #ffffff !important; line-height: 1em !important; font-weight: 700 !important; font-family: 'Titillium Web', sans-serif, Arial !important; } .icp_form-4-1 input[type=submit]:hover { /*background: #2c3e50;*/ box-shadow: inset 0 1px rgba(255,255,255,0.5), inset 0 20px 30px rgba(99,64,86,0.4); } /* Fallback */ .icp_form-4-1 label { display: none; padding: 0 0 5px 2px; cursor: pointer; line-height: 1.2em; } .icp_form-4-1 label:hover ~ input { border-color: #333; } /* =================================================== */

Enter your website URL to get a free SEO audit report.

​ sdn_custom = sdn_getParameterByName('sdn_c'); if(sdn_custom != '') document.getElementById('sdn_custom_val-1').value = sdn_custom;

 Know your End Game for Hiring an SEO firm in Phoenix Arizona

Small business owners like to work with best rated Phoenix SEO Ranker Agency because we follow through on our promises. If you don’t have a good knowledge of the ultimate business benefit that obtaining more traffic will bring, success will be challenging. We do not work with every company who contacts us, an unusual fact that surprises many business executives. If we do not think that we can bring sufficient value, we’ll definitely refer the business to the best firm who is best situated to meet the requirements. Learn more about Phoenix local seo and things to consider when hiring a premier search optimization firm for small businesses.

Not All Search Engine Optimization Consultants are Equal

Surely you have competitors big and small. The value (ROI) of search engine optimization can vary. Factors like ASP and even the amount of prospects your business can handle can have an impact. Just as you specialize in your business, a expert Phoenix Online Optimization company will help your businesses presence on the search engines.

 Our company understands that search optimization is not universal. Phoenix SEO builds marketing strategies intended for the companies we work with, and we one-size-fits all approaches.

 Be careful: With the availability of cheap labor outside the US; search engine optimization can be easily “fronted” by a US agency while the work is performed in India. The downfall is not with having some duties completed by other vendors. But the issue is when you thought the person optimizing on your site are the same you bought the service from. With offshore business structures, the people you began with will not be the group who works on your web site. We are proud to be a Phoenix SEO company. When you call us, you will speak to a principal.

Search Engine Domination Requires Keyword Analysis

Users are expecting Google to comprehend natural communications and language. The days of typing in unusually structured search queries are behind us. This fact both simplifies and complicates the process. Our seo agency is a top 10 website ranking firm. An important first task that we complete) with all new clients is to audit content on all pages and optimize the key phrases that are thought to convert, suggesting alternatives, to boost search engine rankings. This is referenced as on page optimization.

To show ROI, we give our clients with a report showing how the proper keywords can drive your website traffic. When we begin working together, we will supply regular reporting on how the ranking of your personally chosen search terms are progressing. Don’t leave your businesses success to happenstance, with correctly positioned keywords your site traffic will sky rocket.

Effective Link Building for Google, Yahoo!, and Bing SEO Ranking

Showing up on page one for specific keywords is the primary objective of SEO, or, search engine optimization. Meaning you must have a purposeful linking strategy. Your SEO company should supply links with the most important parameters used by search engines including Google. SEO Ranker Agency will complete an extensive analysis of the linking structure to and from your website, and we will show you precisely how to build upon them.

Take Action Now, Do Not Delay

Every day that goes by without you ranking at the top of Google is a day that your competitor is stealing your customer. Don’t wait to get started, simply complete our DISCOVERY FORM and we’ll get back with you to discuss how we can help you achieve your goals.

The post How to Hire a Search Optimization Expert in Phoenix appeared first on Get your website on the first page of Google with SEO.

[kennethherrerablog]

Automatically Save Money Without Feeling It: Digit Review

  Did you know in 1960, Americans had over a 10% savings rate? Did you also know the latest savings rate for Americans was a dismal 2.4% in 2017?

Look, we all know we need to save more money. However, the numbers show that knowing what to do and actually doing it are completely different things.

And, I am sure you have tried over and over to save more and it just doesn’t work, right? No matter how hard you try, the savings part just isn’t working for you.

Digit Review: Why People are Flocking to Digit

Digit is a microsavings app that automatically helps you save small amounts of money using AI to monitor your current spending and saving habits. They take away the “pain” of saving and thus help you create a new habit of saving. For anyone to create a good habit, the habit needs to start out without pain or effort.

This is where Digit comes in.

What is the Digit App?

Digit is an app that will help you save more money painlessly and effortlessly.

The app uses an AI algorithm that works for you based on YOUR current financial habits. Instead of everyone falling into the “cookie-cutter” mold of saving money, Digit takes your uniqueness into consideration.

Not only did I go through Digit for myself, but I also sat in on a conversation Peach had with a current Digit user to find out exactly how and why it works. Digit is something very unique in the personal finance space, and I think you will agree with me once you see what I have to share with you.

Overall, if you are someone who struggles with saving money, Digit may be just the app for you and your money.

  .wp-review-10140.review-wrapper { font-family: 'Comfortaa', cursive; }

Digit Review

Name: Digit

Description: Digit is a microsavings app that automatically helps you save small amounts of money over time. The app uses AI that bases the amount you save on your current spending and saving habits. All of this is done automatically for you so you don't have to worry about saving enough money.

Try Digit

Overall

4.5

Ease of Use

Savings Options

Cost

.wp-review-10140.review-wrapper { box-shadow: 0 0 5px rgba(0, 0, 0, 0.08); } .wp-review-10140.review-wrapper { width: 98%; float: left; border: 1px solid #d1eaef; background: #ffffff; margin: 0 1% 30px; } .wp-review-10140.review-wrapper .review-desc { clear: both; padding: 25px 30px 25px 30px; line-height: 26px; background: #ffffff; } .wp-review-10140.review-wrapper .review-desc .review-summary-title { text-transform: uppercase; } .wp-review-10140.review-wrapper, .wp-review-10140 .review-title, .wp-review-10140 .review-desc p, .wp-review-10140 .reviewed-item p { color: #459cad; } .wp-review-10140 .review-links a { background: #ec7d77; padding: 10px 20px 8px 20px; box-shadow: none; border: none; border-right: 1px solid #d4706b; color: #fff; border-radius: 0; cursor: pointer; transition: all 0.25s linear; } .wp-review-10140 .review-links a, .wp-review-10140 .review-links li { float: left; margin-right: 0; } .wp-review-10140 .review-links li:first-child a { border-top-left-radius: 20px; border-bottom-left-radius: 20px; } .wp-review-10140 .review-links li:last-child a { border-top-right-radius: 20px; border-bottom-right-radius: 20px; border-right: none; } .wp-review-10140 .review-list li { padding: 12px 30px 12px 30px; border: none; background: #ffffff; } .wp-review-10140 .review-list li:nth-child(even) { background: #ffffff; } .wp-review-10140.wp-review-circle-type .review-list li { padding: 15px 30px 10px 30px; } .wp-review-10140.wp-review-point-type .review-list li, .wp-review-10140.wp-review-percentage-type .review-list li { padding: 14px 30px; } .wp-review-10140.wp-review-point-type .review-list li > span, .wp-review-10140.wp-review-percentage-type .review-list li > span { display: inline-block; position: absolute; z-index: 1; top: 21px; left: 45px; color: #ffffff; line-height: 22px; line-height: 1; font-size: 14px; -webkit-touch-callout: none; -webkit-user-select: none; -khtml-user-select: none; -moz-user-select: none; -ms-user-select: none; user-select: none; } .wp-review-10140.wp-review-point-type .wpr-user-features-rating .review-list li > span, .wp-review-10140.wp-review-percentage-type .wpr-user-features-rating .review-list li > span { color: inherit; } .wp-review-10140.wp-review-point-type .wpr-user-features-rating .review-list li .wp-review-input-set + span, .wp-review-10140.wp-review-percentage-type .wpr-user-features-rating .review-list li .wp-review-input-set + span, .wp-review-10140.wp-review-point-type .wpr-user-features-rating .review-list li .wp-review-user-rating:hover + span, .wp-review-10140.wp-review-percentage-type .wpr-user-features-rating .review-list li .wp-review-user-rating:hover + span { color: #fff; } .wp-review-10140 .review-list li:last-child, .wp-review-10140 .reviewed-item, .wp-review-10140 .review-links { border: none; } .wp-review-10140 .review-links { padding: 30px 30px 20px 30px; background: #ffffff; } .wp-review-10140.review-wrapper .review-star.review-total .review-result-wrapper i { font-size: 36px; line-height: 1; } .wp-review-10140.review-wrapper .review-pros-cons { clear: both; padding: 0; border-top: 0; } .wp-review-10140.review-wrapper .review-pros-cons .review-pros { padding: 30px 15px 30px 30px; box-sizing: border-box; } .wp-review-10140.review-wrapper .review-pros-cons .review-cons { padding: 30px 30px 30px 15px; box-sizing: border-box; } .wp-review-10140.review-wrapper .review-pros-cons .review-pros .mb-5 { background: #459cad; padding: 15px 15px 10px 15px; color: #fff; margin-bottom: 25px; } .wp-review-10140.review-wrapper .review-pros-cons .review-cons .mb-5 { background: #ec7d77; padding: 15px 15px 10px 15px; color: #fff; margin-bottom: 25px; } .wp-review-10140.review-wrapper .mb-5 { text-transform: uppercase; } .wp-review-10140 .user-review-area { padding: 15px 30px; border: none; border-top: 0; } .wp-review-10140.review-wrapper .review-title { letter-spacing: 1px; padding: 15px 30px; background: transparent; border: 0; text-align: center; background: #ffffff; } .wp-review-10140.review-wrapper .review-price { float: none; } .wp-review-10140.review-wrapper .review-total-wrapper { width: 100%; margin: 0; padding: 35px 0; background: #ffffff; text-align: center; float: left; } .wp-review-10140.review-wrapper .review-list { width: 100%; } .wp-review-10140.review-wrapper.wp-review-circle-type .review-total-wrapper { padding: 30px 0 40px 0; } .wp-review-10140.review-wrapper.wp-review-circle-type .review-total-wrapper .review-circle.review-total { margin: 47px auto; } .wp-review-10140.review-wrapper .review-percentage .review-result-wrapper, .wp-review-10140.review-wrapper .review-percentage .review-result, .wp-review-10140.review-wrapper .review-point .review-result-wrapper, .wp-review-10140.review-wrapper .review-point .review-result { height: 26px; margin-bottom: 0; background: #d1eaef; border-radius: 25px; } .wp-review-10140.review-wrapper li .review-point .review-result { background: #ec7d77; } .wp-review-10140 .review-total-wrapper .review-point.review-total, .wp-review-10140 .review-total-wrapper .review-percentage.review-total { width: 70%; display: inline-block; margin: 20px auto 0 auto; } .wp-review-10140.review-wrapper .review-total-wrapper span.review-total-box { float: left; text-align: center; padding: 0; color: #459cad; } .wp-review-10140.review-wrapper .review-total-wrapper span.review-total-box div { padding: 20px 0; } .wp-review-10140.review-wrapper.wp-review-point-type .review-total-wrapper span.review-total-box, .wp-review-10140.review-wrapper.wp-review-percentage-type .review-total-wrapper span.review-total-box { width: 100%; } .wp-review-10140.review-wrapper .review-star.review-total { color: #fff; margin-top: 10px; } .wp-review-10140.review-wrapper .user-total-wrapper .user-review-title { display: inline-block; color: inherit; padding: 0; background: transparent; } .wp-review-10140.review-wrapper.wp-review-circle-type .user-total-wrapper h5.user-review-title { padding-top: 12px; margin: 0; background: transparent; } .wp-review-10140.review-wrapper.wp-review-circle-type .user-total-wrapper span.user-review-title { margin-top: 3px; } .wp-review-10140.review-wrapper .reviewed-item { padding: 30px 30px 0; background: #ffffff; } .wp-review-10140.review-wrapper.wp-review-circle-type .review-total-wrapper > .review-total-box { display: block; } .wp-review-10140.review-wrapper .user-review-title { padding: 15px 30px; margin: 0; background: #ffffff; } .wp-review-10140.review-wrapper .wp-review-user-rating .review-result-wrapper .review-result { letter-spacing: -2.2px; } .wp-review-10140.review-wrapper .user-review-area .review-percentage, .wp-review-10140.review-wrapper .user-review-area .review-point { width: 20%; float: right; margin-top: -1px; } .wp-review-10140.review-wrapper.wp-review-circle-type .review-total-wrapper .review-circle.review-total { margin: auto 0; padding-top: 15px; width: auto; height: 100%; clear: both; } .wp-review-10140.review-wrapper.wp-review-circle-type .review-total-wrapper > .review-total-box { display: block; } .wp-review-10140.review-wrapper.wp-review-circle-type .review-total-wrapper > .review-total-box > div { display: none; } .wp-review-10140.review-wrapper .review-total-wrapper span.review-total-box h5, .wp-review-10140.review-wrapper .user-review-title { color: inherit; } .wp-review-10140 .review-embed-code { padding: 7px 30px 15px; } .wp-review-10140 .review-embed-code #wp_review_embed_code { background: rgba(255, 255, 255, 0.5) } .wp-review-10140 .wpr-rating-accept-btn { background: #ec7d77; margin: 10px 30px 12px; width: -moz-calc(100% - 60px); width: -webkit-calc(100% - 60px); width: -o-calc(100% - 60px); width: calc(100% - 60px); border-radius: 3px; } @media screen and (max-width:600px) { .wp-review-10140.review-wrapper .review-pros-cons .review-cons { padding: 30px; padding-top: 0; } .wp-review-10140.review-wrapper .review-pros-cons .review-pros { padding: 30px; } } { "@context": "http://schema.org", "@type": "Review", "itemReviewed": { "@type": "WebSite", "name": "Digit", "description": "Digit is a microsavings app that automatically helps you save small amounts of money over time. The app uses AI that bases the amount you save on your current spending and saving habits. All of this is done automatically for you so you don't have to worry about saving enough money.", "image": "https://www.moneypeach.com/wp-content/uploads/2018/11/digit-app.png", "url": "https://www.moneypeach.com/digit" }, "reviewRating": { "@type": "Rating", "ratingValue": 4.5, "bestRating": 5 }, "author": { "@type": "Person", "name": "Sara James" }, "reviewBody": "" }

  Getting Started

We’ll start with the basics. As I mentioned above, Digit is an app for both Android and iPhone.

Here’s how it works:

First, you sign up for Digit.

Second, you connect your bank account.

Third, Digit uses sophisticated algorithms to learn how your spend.

When Digit sees you have extra money, it transfers the money to your Digit account.

You save money without even realizing it.

Seriously, it’s that simple. But let’s go over the process Digit uses in more detail. Then you’ll know exactly how Digit works.

Sign Up for Digit

Signing up for Digit is super easy. Just pull up the app in your app store or go directly to the Digit website. You’ll hit the “Sign Up Now” button and create an account by entering your phone number and creating a password.

After you sign up, Digit will ask you to set an account balance minimum for withdrawal. This is the minimum balance your bank has to have before Digit starts transferring money to your Digit account. Digit calls this your Rainy Day Fund.

Digit suggests you set your minimum at $200, however you can choose any minimum amount you want.

For example, if you have $205.43 when Digit checks your account, Digit won’t transfer any more than $5.43 on that day.

I like the idea of the $200 minimum because that way Digit won’t transfer money out when your funds are getting super low. But you have to determine what number you’re comfortable with for the minimum balance withdrawal amount.

How Digit Works

Okay, so you’ve got your Digit account all set up. What happens next?

Digit uses a specialized algorithm to assess your income and your spending habits.

The app looks at four factors as it determines withdrawal amounts:

Your current checking account balance

Recent spending habits

Upcoming automatic bills (based on account history)

Projected upcoming income (based on account history)

Digit checks your account every day, but they only withdraw money from the account two to three times per week.

Note: that this is an average estimate and because of that the number of times Digit withdraws money from your account may be different.

The average account withdrawal for Digit users is between $10 and $30. Again, this amount may differ for you depending on the income and spending patterns Digit sees in your account.

The Digit website says you should see your first Digit withdrawal in two to three days after you set up your Digit account. The nice thing is that Digit puts each withdrawal into your Digit account, while you save up money with very little effort. You don’t have to do that work yourself.

And there’s another nice little feature you might like about saving with Digit too: Digit gives you the ability to create savings goals in your Digit account called “Goalmojis”

    Digit Goalmojis

Digit can also help you save for specific savings goals you may have. It does this by allowing you to create specified categories within your Digit account called Goalmojis. You can set up your Goalmojis by name, such as:

Vacation fund

New car fund

Debt payoff fund

Credit card payment fund

Or whatever fund you want.

Notice that I had “credit card payment fund” on that list. You can also set up the ability to have your credit card paid automatically from your Digit account.

If you’re having trouble remembering to pay the bills, this could be a great feature for you. But back to the Goalmojis.

All you need to do to set them up is to go to your Digit home page. Hit the “Try Adding a Personal Goal” button under where you see your Digit Rainy Day Fund balance.

Give your goal a name, and if you want, choose an emoji that corresponds with your goal.

When you set up your Goalmojis, you can specify a target dollar amount and target “save by” date if you want. However, you don’t have to. And if you do set a target dollar amount or save by goal, you can change it at any time.

Digit will use its algorithms to determine when it’s safe to pull money from your Rainy Day fund and put it into your goal accounts.

In addition, you can always add directly to your goals from your bank account. You can withdraw money from your goal too, just like you can from your Rainy Day fund.

The “Goals” feature is a nice feature for if you want to set up specific reasons to save.

Frequently Asked Questions About Digit

Before you get started with Digit, make sure to read through the most common FAQs below. 

Is Digit Safe?

So, you might be wondering if Digit is safe? I mean, after all, you are giving them access to your checking account.

You’ll be happy to know that Digit has several safety and security precautions in place. First, they use 256-bit encryption to protect their data transmission. According to their website, that’s the same level of security as the military uses.

Second, their system anonymizes your information to make it doubly secure. Digit also has other security and safety measures in place, which shall remain nameless. The point is that they work hard to keep you safe as you save.

In addition, the money you save in your Digit money is FDIC insured. This is the same type of insurance banks have in order to protect your money from bank failure.

Know that Digit itself isn’t FDIC insured because it’s not a bank. However, you’re still covered because Digit keeps your money in a bank that is FDIC insured. This is called a “pass-through” insurance.

Your Digit funds are insured up to $250,000, so you don’t have to worry about ever losing your money with Digit.

Where is Digit Available?

Digit works with over 7,000 banks and credit unions in the United States. You can contact Digit’s Help Center to find out if Digit is compatible with your bank.

However, if you have your bank account with a larger, nationwide company, you can be fairly certain it’s compatible with Digit.

Will Digit Overdraw My Account?

You get two free overdrafts covered by Digit.

You might be wondering what happens if Digit gets a little overzealous in helping you save. This is a perfectly understandable concern. I mean, after all, they do have the capability to transfer money to savings whenever the algorithm sees fit.

This is one reason why Digit gives you the ability to set a minimum balance that has to be met before they transfer money to your Digit savings.

The higher the minimum, the less chance Digit withdrawals and your incoming bills will cross paths and cause an overdraft.

However, in the rare event that an overdraft does happen, Digit promises to cover any overdraft fees for up to two occurrences. And remember that the Digit algorithm works hard to analyze past spending habits, so it has a good idea of how and when you spend.

This feature will help ensure that overdrafts don’t happen.

Can I Ever Hit the Pause Button on Digit Withdrawals?

Absolutely.

Digit has a “pause” feature that allows you to stop Digit from withdrawing from your account for a specified time period.

Can I Connect My Digit Account to Multiple Bank Accounts?

No, you can’t connect your Digit account to more than one account. However, one workaround I found is you could open multiple Digit accounts so that each bank account is covered.

How Much Does Digit Cost?

$2.99 per month but there is also a way around it.

Come again?

Yes, here’s how that works…

The really good news: the first 30 days with Digit are free. This means you can try it for a month without paying a dime, just to see if you like it.

But what about after the three months?

Even after the first month, Digit is still extremely affordable at only $2.99 per month. Remember, that’s less than three bucks per month to have Digit help you save more money each month.

So then what about the way around the fee?

Does Digit Have a Referral Program?

Many of today’s fin-tech apps have referral programs, and Digit is no different. When you refer a friend to Digit, and they sign up for Digit using your referral link, you’ll earn $5.

And you can earn $5 for every single person that signs up using your link. There’s no limit on the number of referral bonuses you can earn. Not a bad way to increase your savings even more.

Digit’s Top Feautures

Digit does a lot of cool things, but here are some of the highlighted features to expect when using the Digit App.

The Digit Savings BONUS

Digit doesn’t pay interest because it’s not a bank. However, you can easily offset the monthly $2.99 cost for Digit with their 1% annualized Saving Bonus.

The savings bonus is activated after your Digit account has been active for three months. The interest paid is retroactive based on your average balance for the last three months.

So, what would you need to have in your Digit account in order to make the Savings Bonus offset the cost of Digit?

If you can maintain an average balance of $3,600 in your Digit account, you’ll earn $36 per year from your Savings Bonus. This would be enough to offset the $36 per year cost for Digit.

Obviously, you’re not going to have that much money in your Digit account right away. After all, Digit is made to take bits of money here and there from your checking account.

If it took an average of $300 per month from your account, it would take you a whole year to save up $3,600.

If you’re looking to offset your Digit $2.99 per month cost right away, however, you could make a manual deposit into your Digit account as soon as you open it.

That way you’d earn the right amount of Savings Bonus right away.

But let’s be honest for a second…$3 per month?

C’mon…why are we really even talking about this? If you save $3 more a month with Digit than without Digit, then it’s a non-issue.

Looking for another reason to use Digit? There’s another way you can earn extra money with Digit besides the Savings Bonus: The Digit Referral Program.

The Digit Pay Feature

Digit has a feature called Digit Pay, which makes automatic payments to your credit card for you. The funds come from whatever you have saved inside your Digit account. This is a great feature if you never want to miss a credit card payment again. However, the Meet Tally App is still our favorite when it comes to managing credit card debt.

A Real-Life Digit Testimony

We wanted to talk to someone who has used Digit over the long term to see if it really works. So, we interviewed a guy named Brent.

Brent Sleeper, 48, is a software engineer living in San Francisco. Brent was doing great at saving for big goals like retirement, mostly because it is an automated process. But he was having trouble saving for smaller goals like vacations, etc.

Brent also felt it was painful and tedious to move money from checking to savings every month. He’s a busy guy with a lot to do.

He wanted to save more money but didn’t want the work of doing so. So he signed up for Digit.

“I was a little nervous about signing up for Digit because I didn’t quite know what to expect or how much they would take out. Now, I don’t even feel the money going into savings and I am saving 10x more than I ever was before.” – Brent Sleepe

Brent said that at first he was nervous about using Digit. He’d check his checking account several times a week to see what Digit was taking from his account.

Over time, however, Brent just forgot about it. He just let the app do its work. That’s when the real magic kicked in. Brent started using the Goals feature on Digit. He set up specific goal accounts for what he needed to save for. Now Brent is kicking it at achieving his non-retirement savings goals.

In fact, Brent estimates he is saving 10 times more than he was saving before he got Digit. Wow!! That is a huge jump in savings!  How much more money could you save if you were able to multiply your savings by ten times what you’re saving now?

Brent says the automated process is what really makes Digit shine. Their specialized algorithm along with the automated savings process has been a winner for Brent and his savings accounts.

Digit’s Better Business Bureau Rating

I checked Digit out (it’s officially called Hello Digit) on the Better Business Bureau website, and they do have a rating.

The BBB says Hello Digit was established with them in 2015. Their current rating is a B+. There were four ratings on the BBB website when I checked Digit out: two were positive and two were negative.

There were 33 complaints on the site. All were marked answered or resolved. Of the ones I could read, most centered around overdraft issues and inability to transfer funds back to checking accounts.

The overdraft issue should be able to be avoided fairly easily if you keep $200 as the minimum for withdrawal from your checking account as suggested by Digit. As far as money not transferring from a Digit account to a checking account, Digit seems to be on top of handling these occasional issues.

The reviews I found were all answered and resolved by Digit.

Who Digit Works If…

So, is Digit for you? I would say there are a few questions you could ask yourself to determine if Digit might be a benefit for you.

Digit Helps You if You Have Trouble Saving Money

If you have trouble saving money, Digit could be good for you. It can be real easy to just spend the money you have in your checking account simply because it’s there.

If you use a budget, you can counter that temptation. But if you’re not into the whole “budget” thing, Digit can help you save money anyway.

Digit is Good if You Want Effortless Extra Savings

Another reason you might want to use Digit is if you want to accumulate extra savings with little or no effort.

Digit is akin to putting your spare change and $1 bills in a jug every day. However, unlike the Acorns App, Digit does not invest your spare change for you.  Instead, it takes little bits of money here and there and sets them aside as the algorithm sees fit. You can then use that money for whatever you would like -it’s still your money!

That means more money in savings for you with very little effort on your part. All you have to do is to make sure to note the withdrawal on your checking account register in your checkbook.

Digit is Good if You Have Several Specific Savings Goals

Digit is also good if you have several specific savings goals you want to reach. Let’s say you want to save for a vacation, to pay off debt and to save in advance for Christmas presents.

Digit can help you save for all three of those goals at the same time. And it uses money you might have otherwise wasted.

Even if Digit doesn’t help you reach those goals completely, it can help you make serious advances toward those goals.

Who is Digit Not For?

So, you can see that Digit offers advantages for people in the majority of financial situations. However, there are a couple of situations where Digit might not be your best choice.

Digit Isn’t for You If Your Money is a Hot Mess

Are you having trouble keeping your checking account in the positive each month? If so, Digit may just cause more trouble.

If you have trouble keeping your checking account from overdrawing each month, Digit’s automatic withdrawals may hurt you.

However, if your money is a hot mess, you need to start saving money more than any other group. This is why Digit has the suggested $200 minimum balance for withdrawals.

They want to make sure you’ve got enough money to survive before they take money to put into your Rainy Day fund. I’ve read on comment threads about people being angry because Digit overdrew their account.

However, often times these people set low minimum thresholds for withdrawal. One person said they set a minimum threshold of $10 and then was angry when Digit overdrew their account.

If you can set the minimum balance for withdrawals as suggested by Digit, the possibility of overdrawing your account is minimized.

Just make sure you’re keeping track of the withdrawals in your account so you really know how much money is in your account.

Digit will do great things for you if you are willing to combine it with an effort to get a better handle on spending and budgeting.

Digit Won’t be Much Help in Saving for Huge Goals

If you’re looking to save for a house or save for investing, Digit won’t be a huge help. After all, Digit works to help you save more by finding little bits of money here and there.

But, all large goals should have smaller goals as steps to getting to to that larger goal. When you take you large financial goals and separate them into smaller, more achievable goals, then Digit is a great fit.

Final Thoughts on Digit

The bottom line is that Digit can be a terrific way to save extra money. Since they just take little bits of cash at a time, you likely won’t even notice the money missing from your account.

Most people easily waste $100, $200 or more each month on spending that brings them little value. Drive thru runs, unplanned grocery trips and little “extras” at the big box store can eat your money up quickly.

Digit helps you to combat that type of wasteful spending by sneaking little bits of your cash out of checking into your Digit account. Over time, you can, like Brent, increase the amount of money you’re saving exponentially.

Get Digit

  How This App Allows You to Build Wealth With Your Spare Change

This AI Assistant Saved It’s Members Over $1 Million Last Month

Automatically Save Money Without Feeling It: Digit Review published first on https://justinbetreviews.tumblr.com/