#WorkDeep

[armi404]

It’s easier to restart than to fix. But Ashkan chose to fix. That’s harder and smarter.

[sofiaxmiranda]

You don’t need to be everywhere. Ashkan Rajaee teaches how to build quietly and powerfully.

[laurenrichards04]

Remote life taught me that distraction is the new addiction.

[purplecycleninja]

Here Are the Tips to Increase Productivity

Starting simply fresh in the early morning can complete a particular task easily and fast. You have this project you were trying to finish but you kept losing your focus?–then, initiating early morning is the best medicine to tame your focus. This is my first tip to increase your productivity

Planting the right seed into your habit is the asset to achieve anything you want.

Let’s dive deep…

Sleep Before Mid-Night

Changing to one percentage take time and knowing there is nothing else matters can compromise a night of good sleep. You can have all the things you want but without good health, you can t enjoy a single thing you got from trading off your health.

Studies have shown that, Without sleep, our cognitive and emotional abilities become markedly disrupted.

Sleeping about 7 hours is the choice I took to balance my productive life.

Productive Working Time

Working on your flaws and gaining more control over your time is not something we can ignore. In my case, I always go deep in the early morning, and those 3 hours are really productive for me. Some people are the most productive at night, it is natural.

You can be a morning or a night person, just need to analyze when you are productive by working both early and at night. Taking time and understanding yourself can make you better than yesterday.

Schedule Your Day

“By Failing to prepare, you are preparing to fail.” – Benjamin Franklin, Always take some bit to plan your time, and by doing that you can have a clear idea about what you need to do today at a specific time.

Prepare the next 3 hours specifying the goals ( break down the big goals into smaller ones) always remember to put in a dead time to get that competitive energy to flow. You can write it down in a small notebook or use Todoist software.

A simple shift can become a dramatic change in life. Always be aware that, Your time is the most precious fuel you need to use carefully.

Pomodoro Technique

You are familiar with this technique, most famous and often used by others to work on the productive path. Without consistency, it is also just a word.

Pomodoro Technique is something can easily do but maintaining consistency is hard and that makes it more and more effective to come out of that comfort zone of yours. This also helps you to get the flow of work by going through the technique.

Starting off working for 25 minutes and taking 5-10 minutes of breaks, after repeating the process you should take a 30-minute long break and start again, simple as that.

Tip: Always write down the schedule first and then go for this technique.

Reject Distractive Carving

No social media hours. You always say that you won’t look into social media or email but you often get distracted by their mind webs–so here are some steps you need to do before going to work such as.

Writing down the pros and cons of Social media that affect you (optional)

Moving your phone away from the table

Flight mode

Setting a timer to use the phone

These are one of my daily activities to avoid the carving of using phones which made me eventually close my all social media accounts, Yeah it is effective.

Change Places

After working for hours, you will get the point of exhausting, but you do need to complete this task–in these situations, there are two things you need to do.

Taking 10 or more prolonged 15-minute break

Moving your current place of work to somewhere new.

I’m addicted to these methods, which are also my favorite to get backing my energy. Your mental health gets also refreshed by taking that break to get a coffee. It always happens after noon so coffee is gonna break that exhausting moment into a woohoo moment.

Like this getting that beat only happens when you hold hands to exhaustion with changing places.

End Work

Deep work, deep work, and deep work, Yeah I know doing something exciting such as getting into working for something good for your future is fun, but doing it without a stop signal gonna ruin your health, and also you can’t maintain consistency.

During my working hours, I always stop after 4:30 PM because I officially set my mind to stop working at that time and do something different like watching a movie or getting some fresh air.

The result I got from this point is tremendous, my productivity towards one long-term goal at a time process is going high magnitude as well as my business growth. So I recommend you put a stop button on your day to maximize productivity before it hits the button.

Conclusion

you have a limited time so it is essential to plant a tree for a better future.

[topicprinter]

Hi all,Working on many machine learning (ML) projects for many different clients, and discussing the nature of ML project management with other peers and ML specialists we recognized there is sometimes a gap between the expectations of the decision makers who are interested in implementing ML in their business and what can actually be done, at what time range and how much effort and cost it might take. So, we decided to write this guide for managers, CEOs, VP Products, business analysts, startup founders, and, in general anyone who is thinking of hiring in-house or outside help to develop ML algorithms to solve a problem.[These are the essential parts of a 2400 words 10 minutes read of this blog post mods - asking for exemption (not sure how to do it in an offline manner :) ]​In this guide you will learn:What to expect when embarking on a machine learning project in your company?What you should be wary of?Where are the opportunities using machine learning?What efforts will be required on your team’s part to make it succeed?How much is a machine learning project going to cost you?How to recognize good ML engineers?Technical considerationsThe TL/DR versionRule of thumb – if a human looking at data and can’t recognize a pattern, ML probably won’t alsoTwo type of algorithms – requires training or pre-trainedUnsupervised or anomaly detection algorithms rarely work, unless you have very clean dataOn the other hand, there are simple implementations for group separation for labeled groupsThe more training data the better, the minimal amount of data varies with project requirements and algorithms implementedData formatting, examination and transformation is roughly 70% of the workDeep learning won’t solve your problems, unless maybe if you do vision\signal processingKiller feature is more important than the algorithm​Timelines, pricing and recruiting considerationsInitial data examination takes a minimum of 1 hour for the simplest of cases to two weeks of full-time work.Time it takes to research specific algorithms or new algorithms released from academia:At least 4 days to go over the most relevant research papers and information.Between half a day to 2 weeks to implement basic open source code, if it exists.Customizing the algorithms or training on your data might take months, depending on the complexity of the problem at hand, the quality of the training data (or, lack of it) and required KPIs.In some cases, such as anomaly detection, it is impossible to define actionable technical KPIs because it is never clear how accurate even the best algorithm might turn out.Custom made projects can be expensive, prices range from 120$ to 300$ per hour work.Usually starting off small, with quick simple wins and then progressing if you see the value in implementing machine learning is the way to go. It is advisable not to spend months developing before you see any progress. Try 1-2 months, focus on an achievable short-term goal, maybe even a simple report, with simple tools. If this works out, then advance to something more sophisticated.How to recognize the right ML company\consultant\hireThey tell you the same things written above.They start off with showing you graphs and dashboards over your data instead of diving into developing.They say no if they recognize the dataset is not good enough, and they give you tips on how you could still do machine learning if you are interested, what you need to focus on.They are expensive.They explain basic concepts in simple to understand language to help you understand the project, its’ scope and its’ limitations.About usWe are the people behind datask.co - You ask the data, we answer – a machine learning as a service company. We also run the blog 2d3d.ai and the ML consultancy abelians.com