#alg resources

[rigelmejo]

What is Automatic Language Growth?

For some reading material on what Automatic Language Growth theory is, see this article from Mandarin from Scratch, ALG in a Few Words from Dreaming Spanish, and Marvin Brown's book about ALG. Marvin Brown is who theorized Automatic Language Growth.

I do not agree 100% with ALG theory, it has not been tested much (like many language learning theories). It's claims have not been studied enough. Students who have done ALG certainly learn the language, so it is at least a successful approach (among many approaches people successfully use). Pablo from Dreaming Spanish is an example of ALG successfully working, he did ALG classes to learn Thai, and his lessons at Dreaming Spanish have resulted in many people learning Spanish to a decent level (see r/dreamingspanish for various learners progress reports and results).

I would suggest if anyone is curious about trying Automatic Language Growth to either:

1. Check out Comprehensible Thai on youtube. Since there is enough comprehensible input lessons for Thai to go from nothing to functional in the language. Thai is where ALG programs started, so there's also multiple language schools that do ALG in Thailand and online that offer lesson sessions. On reddit, user whosdamike has documented his progress learning Thai through ALG. So there's someone you can specifically look at, to see the potential results and path to progress. Note: r/ALGhub is very dogmatic about strictly adhering to ALG, and its possible a school focused on ALG specifically will also be quite strict about adhering, if you choose to take ALG school classes.

2. Check out Dreaming Spanish. They have a free youtube channel, and more paid lessons on their website. Their website has a guide on how to do an "ALG like" approach with the material Dreaming Spanish makes, and a Roadmap to help you gauge your progress. I would say Dreaming Spanish suggests learners do an ALG approach, but they do offer suggestions for if you want to read or speak earlier than ALG recommends, and they do not worry about "permanent damage" from prior study (as MANY Dreaming Spanish learners already have some experience learning Spanish before they find Dreaming Spanish).

On reddit r/dreamingspanish has a lot of people sharing their progress, and you can find many people who reached B2 and some who reached C1 level in Spanish. You'll find some did a "purist" stricter ALG approach, and some just used the Dreaming Spanish Comprehensible Input Lessons along with other things. So you can see their progress and what they did, and decide for yourself how strictly you want to do ALG or if you want to include other things like some people do. The r/dreaminglanguages and r/dreamingspanish subreddit have various people doing a study approach similar to ALG, while still including many people who deviate to some degree. So those subreddits will all be more welcoming to you if you choose to do something outside of ALG/against ALG ideas. Whereas the r/ALGhub is very dogmatic and assumes all people are very strictly adhering to ALG ideas, and will reject any suggestions to deviate.

As a note, r/languagelearning can be quite hostile to learners doing strict ALG, and learners doing the "purist" Dreaming Spanish route. So you will not get much discussion about ALG on that subreddit.

3. Check out Comprehensible Input Wiki, and use the Comprehensible Input Lessons linked there as a starting place to look for more stuff you understand the main idea of, in the language you're learning. You can use the Dreaming Spanish roadmap as a guide for how to study in an ALG way, if you want to try out an ALG approach.

If you don't care to specifically do ALG and just want to use primarily comprehensible input to learn a language: you can just use comprehensible input lessons, learner podcasts, and graded readers, in combination with whatever other study materials you want to use. Many people on r/dreaminglanguages are pretty much finding enough CI lessons, graded readers, learner podcasts, and cartoons for toddlers to learn the basics, then watching/reading/listening to stuff they understand the main idea of in the target language, and doing some other stuff depending on the person.

Time to learn a language: regardless of if you do an ALG approach, the Dreaming Spanish Roadmap and FSI Estimates to Learn a Language (count by class and self study hours so 40 hours for each week estimate), are both good guides for estimating how many hours of study to aim for to reach your goals.

Dreaming Spanish Level 7 is around B2 if you practice speaking 100-200 hours and read 1 million+ words, which the roadmap recommends. FSI Estimates are around B2 as well. So for languages similar to ones you know, estimates to B2 are around 1200-1500 hours. For languages extremely different from ones you know, B2 is around 3000 hours (Dreaming Spanish) to 3520 hours (FSI Estimate). Keep in mind that these estimates may be a bit shorter than the average, so some people can expect to add 500-1000 hours. So for pretty much any language, estimates range from ~1200-4500 hours you'll expect to put in. Regardless of if you take the Dreaming Spanish comprehensible input estimate, or the FSI traditional study estimate. Regardless of if you learn a language similar to one you know, or very different to one you know, you can expect at least 1000 hours must be put into learning. So keep that in mind when making a study plan and goals.

(A note on estimates: Dreaming Spanish estimates that if a language is Very similar to one you know, and/or you have learned a language before, then the roadmap estimates can be halved. So it's possible a French speaker learning Spanish would only need 750 hours to learn Spanish to B2 level. Or if an English speaker who learned French, and then learned Spanish then Spanish may only take 750 hours. So you can reduce the estimated hours to learn a language down to several hundred hours - instead of a thousand or more - if you already know a Very similar language).

[pepsin26]

The winged... wait, that isn't a demon!

Tanjiro was falling from the sky. Its happened it's fair share of times after the battle against upper six. Apparently the corps wasn't in a position to promote Tanjiro, Inosuke and Zenitsu to hashira officially. But they had basically all the resources and half the respect without the official title. Things had been hectic to say the least. Higher respect from the master meant harder missions. Harder missions meant sticky situations. Such as fighting a demon that could condense clouds to avoid burning in sunlight and fly in the air among other things.

"HINOKAMI KAGURA!"

Oh right he was falling to his death. See instead of just dying this demon decided to try and take Tanjiro down with them. Via using a cloud to blast him as high as possible. Which of course was a very bad thing for our protagonist. His only hope was to spam breathing technique after breathing technique to attempt to break his fall. Which was having varying results of effectiveness.

*THUD*

Everything hurt. But hurt was good. That meant he hadn't died on impact or suffered enough damage for his body to go into shock. His eyes fluttered slightly. No, he had to stay awake. He was probably concussed, so sleeping would be a bad idea, but his muscles felt like led... One s.all nap couldn't hurt, no the... the others were waiting for him, Nezuko was counting on him. He... had to... stay... awake...

Tanjiro didn't stay awake. That was obvious the moment he woke up. He wasn't in the butterfly mansion, or even a wisteria house. He was in a cave. The walls were painted with bio-luminescent alge and flowers that made the walls shimmer with purples, golds, tears and greens. There were rocks settled around the cave almost like furniture. Sitting on of top them were, goblets, shoes, necklaces bedazzeled with jewels some of which were pi ked out of place, shovels, hoes, broaches. Magnified glasses, interesting looking rocks and sticks.

Essentailly any nick knacks, trinkets and other things people may consider "rubbish" were organised around the place. This was definitely not a corps location.

Suddenly Tanjiro hears a small shuffle... he hadn't smelled a demon, or anything of that manner. No this was unique. Not human definitely not. But this was no demon either

He turned and found an alcove that seemed to lead towards the open sky of the mountain. The demon slayer caught sight of a silluette. It was vaguely human but... the hands looked much to sharp and taloned rather than the soft flesh of human skin. Sharp fangs sat in it's maw, bared only for a moment.

Though most notably were grand raven black wings the tips rowed with gold and purple rows of feathers on it's back. It was tall, it stood at twice Tanjiro's hight. It's eyes glowed a bright against the darkness, purple irises assessing Tanjiro curiously... Cautiously.

_______________________________________

[catsushinyakajima]

i see math major 👀 i have to take brief calculus in the fall after not taking a single math class in 5 years… any tips to not overwhelm myself??

hi! okay sorry for the late response, I was gearing up to respond throughout the week and drafting good advice. disclaimer: I wrote A LOT. I promise it's not very scary and if it feels overwhelming, please digest it in bits. I just yap a lot and I wanted to cover all my bases.

Five years is a long time without math and enough time to forget lots of things! It's good that you're getting a good head start so there's no need for you to worry.

I'd start by practicing basic algebra: systems of equations, algebraic expressions (solving for x and stuff), linear/quadratic/exponential equations, etc. I will say, even if you once knew how to do this and used to be very good at it, there is a chance that you forgot a lot and lost your touch. Do not be deterred by that. It is OKAY. I've taken many levels of calculus, didn't take any math for a year, and then completely forgot how to factor an equation. It just happens- math is something you have to work your way back into by making a habit of it.

Then you should review trigonometry, more advanced algebra topics, etc: this is algebra II/pre-calculus. In my opinion, it's just a more extended version of basic algebra. You can review matrices too (part of alg II), but it's not very relevant to calculus unless you're taking differential equations (calc 4). But definitely, DEFINITELY, review trigonometry (sin/cos/tan, triangles, rules for their equations, the UNIT CIRCLE).

I'd say that's a good summary of things to catch up on. Once again, it is okay if you mess up some ridiculously "easy" review problems. It's seriously so, so normal, and it doesn't mean that you're set back too far or have an arduous journey ahead of you. The more you get used to doing math, the more you'll get better at it!

Here's a quick overview of topics taught in calculus I: limits, derivatives, applications of derivatives, integrals, applications of integrals.

If you have time, you could totally look into the topics that'll be taught during your semester too. You're already getting a head start by looking into reviewing things, but this would push you even forward.

Here are links to some free resources for you to use for ANY topic you choose to review (you might know some of them):

Khan Academy: has lots of videos and tutorials. Breaks topics down really well. Has review problems with answers and breakdowns of solutions. The review problems are generally basic compared to in-class test questions, but it's good for building a foundation

Organic Chemistry Tutor: This guy is the goat. His youtube videos are really thorough and he's good at explaining things and he'll walk you through different problems.

symbolab: this is an online calculator that can solve lots of different types of equations, including calculus equations! You can input the most tough, weirdest looking equations with ten variables, and as long a it's solvable it'll give you an answer

desmos: online graphing calculator! It's amazing for visualizing equations and functions.

If you have access to whatever textbook your teacher might use in the fall too, that's also great! Also, feel free to reach out to ME for any math help. I am the biggest math nerd ever so I would probably get excited to help you AHAH. I've done one of my mutuals physics homework before so I promise you wouldn't be overstepping if you asked me for anything else. Good luck on your studies!

[youthmonk1]

How an SEO Agency in Mumbai Can Boost Your Google Rankings

Search engine optimization (SEO) is no longer a luxury; it’s the lifeblood of digital success. Partnering with a seasoned SEO agency in Mumbai can transform your website from an online brochure into a powerful, ranking‑machine that pulls in highly targeted traffic 24/7. Below, we’ll explore how a Mumbai‑based agency elevates your Google rankings—while weaving in essential facets such as web design, content strategy, and technical refinement.

Strategic Synergy of SEO and Web Design Services Dubai

Modern algorithms reward seamless user experiences. A skilled team will audit your site’s architecture and UX in much the same way high‑end web design services Dubai approach their builds—prioritizing speed, mobile responsiveness, and intuitive navigation. By eliminating code bloat, compressing assets, and adopting a mobile‑first layout, the Mumbai SEO specialists ensure lower bounce rates and higher dwell time. Google interprets these positive engagement signals as proof of relevance, subsequently pushing your pages up the results page.

Localized Precision With SEO Service in Mumbai

Search intent often has a hyper‑local dimension: people want restaurants “near me” or lawyers “in Mumbai.” A dedicated SEO service in Mumbai optimizes your Google Business Profile, embeds localized keywords naturally into service pages, and secures authoritative citations from region‑specific directories. Add strategic schema markup—such as organization, FAQ, and local business schemas—and your site gains rich‑snippet eligibility, making your listing more eye‑catching and click‑worthy on SERPs.

Authority Building Through Mumbai SEO Services

Backlinks remain a top‑three ranking factor. Reliable Mumbai SEO services follow an ethical, “white‑hat” outreach methodology—guest posting on industry blogs, earning coverage in niche publications, and acquiring contextual links from influencers. Each relevant, high‑domain‑authority backlink signals trust to Google’s algorithm. Combined with a consistent on‑page content cadence—think in‑depth how‑tos, city‑centric guides, and data‑driven resources—your brand establishes topical relevance, climbing steadily for competitive keywords.

Technical Excellence via Website Development in Mumbai

Your website’s codebase influences crawlability, indexation, and ultimately, rankings. Specialists in website development in Mumbai work hand‑in‑hand with their SEO counterparts to conduct thorough technical audits. They repair broken links, implement canonical tags to prevent duplicate‑content penalties, and configure XML sitemaps for efficient crawl paths. Just as important, Core Web Vitals—Largest Contentful Paint (LCP), First Input Delay (FID), and Cumulative Layout Shift (CLS)—are optimized to pass Google’s stringent performance thresholds. The result? Faster load times and higher positions in organic search.

Content Alignment From Leading SEO Providers in Mumbai

Keyword research is an art backed by robust data tools. Top‑tier seo providers in mumbai map keyword clusters to each stage of the buyer journey. Informational blog posts answer “how,” “what,” and “why” questions; comparison pieces tackle “best” and “vs” queries; and conversion pages focus on transactional intent. By aligning content length, structure, and semantic entities with user expectations, they reduce pogo‑sticking and amplify topical authority. Google’s RankBrain recognizes this alignment, rewarding the site with elevated rankings.

Measuring, Iterating, and Scaling

What gets measured gets improved. An adept Mumbai SEO agency sets up granular tracking—GA4 events, Search Console insights, and heat‑map analytics—to capture performance data. They iterate on-page elements (titles, snippets, internal links) and A/B‑test new call‑to‑action placements. Continuous optimization based on empirical evidence prevents ranking plateaus and keeps your growth curve trending upward.

Future‑Proofing Your Rankings

Google’s algorithm updates roll out several times a year. A forward‑thinking agency monitors SERP volatility, E‑E‑A‑T guidelines, and emerging SERP features (e.g., AI‑powered overviews). By maintaining technical hygiene, refreshing evergreen content, and diversifying traffic sources (news, video, image search), they insulate your rankings from algorithmic shocks.

Final Thoughts

An SEO agency in Mumbai brings a holistic skill set—spanning cutting‑edge UX reminiscent of web design services Dubai, hyper‑local optimization via seo service in mumbai, authority growth through mumbai seo services, rock‑solid foundations powered by website development in mumbai, and data‑driven content crafted by leading seo providers in mumbai. When these elements converge, your website doesn’t just climb Google’s ladder—it secures a durable, revenue‑generating foothold at the top.

Ready to transform your organic presence? Align with experts who treat rankings not as vanity metrics but as catalysts for sustainable business growth.

[nocknocknock]

Google Unveils Groundbreaking AI Architecture: Titans

Google has made a revolutionary leap in artificial intelligence with the launch of its new architecture, Titans, designed to mimic the human brain’s cognitive processes. This cutting-edge technology opens new frontiers in machine learning, greatly enhancing AI efficiency, especially in complex tasks that require vast amounts of data and contextual analysis.

Key Features of the Titans Architecture

The core strength of Titans lies in its unique design, which is inspired by the cognitive processes of the human brain. The model features three levels of memory: short-term, long-term, and permanent memory. This approach allows the system not only to process current data but also to adapt based on accumulated experience. Here’s how it works:

Short-term memory is used to store information needed for immediate tasks. Once the task is completed, unnecessary data is discarded, freeing up resources;

Long-term memory continually learns from new data, updating itself to improve future analytics.

Permanent memory serves as a repository for critical information that the model deems essential to retain.

As a result, Titans not only processes massive amounts of data but also manages its memory efficiently, making the learning process more advanced and organized.

AI Learning Efficiency: A New Era of Performance

One of the standout features of Titans is the integration of parallel data processing. This technology enables the model to handle multiple tasks simultaneously, significantly speeding up learning and improving the accuracy of results. In practical terms, this replaces the cumbersome approaches of the past, saving both time and resources.

Additionally, Titans has already proven its superiority in handling complex computational tasks. The model excels in genomics analysis, time-series forecasting, and other computation-heavy processes, making it invaluable for scientific and medical research. For instance, Titans can accelerate drug development or simulate complex economic scenarios with high precision.

Contextual Analysis: An Impressive Leap in Capability

One of the most remarkable aspects of Titans is its ability to process context on an unprecedented scale. To put this into perspective: the maximum context window for GPT-4 is 4,000 tokens, while Titans can handle a staggering 2 million tokens. This allows the model to analyze information equivalent to 25 books at once and make informed decisions based on this vast amount of data.

This level of contextual processing opens doors to solving problems that were previously out of reach for existing models—from highly accurate forecasting to automated academic writing.

Predictions and Impact on the Industry

The release of Google’s Titans will undoubtedly have far-reaching implications for the AI industry. Firstly, it pushes the boundaries of what AI can achieve, sparking competition among leading machine learning companies. Titans could become the benchmark for complex analytical processes, drastically reducing data processing times.

Secondly, with improved accuracy in predictions and faster data processing, Titans could bring radical changes to industries such as healthcare, science, finance, and even environmental monitoring. For example, Titans could more swiftly calculate optimal paths for reducing carbon emissions or predict economic crises with greater precision.

Conclusion

Google’s Titans architecture represents a monumental advancement in artificial intelligence, poised to reshape how we approach complex problems and industries reliant on data-intensive tasks. With its groundbreaking memory structure, parallel processing capabilities, and vast contextual analysis potential, Titans promises to revolutionize AI, pushing the boundaries of innovation and opening up new possibilities for the future.

The introduction of Titans symbolizes a groundbreaking advancement in artificial intelligence. By combining the power of automated algorithms with the cognitive flexibility inherent to the human brain, Titans ushers in a new era for AI technology. Its large contextual window, efficient memory management, and parallel data processing capabilities make this architecture one of the most significant milestones in AI history. Titans not only opens up vast potential for existing technologies but also unlocks possibilities for innovations in areas that previously seemed unattainable.

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[annabelledarcie]

From Concept to Code: A Step-by-Step Approach to AI Software Development

Artificial Intelligence (AI) is rapidly changing the technological landscape, revolutionizing industries from healthcare to finance, manufacturing to entertainment. AI software development, however, is a multifaceted and intricate process that requires not only expertise in programming but also a deep understanding of machine learning, data science, and problem-solving. Whether you are developing AI to solve a specific business challenge or creating an innovative AI product, the process involves a series of well-defined steps that take you from the initial concept to fully functional code.

In this blog, we will walk through a step-by-step approach to AI software development, covering everything from identifying the problem to deploying the AI model into production.

1. Understanding the Problem and Defining the Objective

The first and most crucial step in AI software development is understanding the problem you're trying to solve. This involves collaboration with stakeholders, domain experts, and end-users to identify their needs, expectations, and constraints. Clearly defining the objective will not only guide the development process but also ensure that the AI solution delivers real value.

Key Activities:

Problem Identification: What specific problem do you want to solve with AI? Is it a classification problem (e.g., identifying spam emails), regression (e.g., predicting sales revenue), or something else?

Stakeholder Involvement: Work with business stakeholders and domain experts to ensure the solution aligns with organizational goals and user needs.

Feasibility Study: Assess the feasibility of using AI to solve the problem. Consider the availability of data, technical resources, and the required computational power.

Why it matters: A clear understanding of the problem and objective is the foundation of a successful AI project. Without this, your efforts may lead to wasted time and resources.

2. Data Collection and Preparation

AI models thrive on data. Once the problem is defined, the next step is collecting the right data. The quality and quantity of the data significantly impact the performance of the AI model. Therefore, data collection, cleaning, and preprocessing are critical stages.

Key Activities:

Data Collection: Gather data from relevant sources (databases, APIs, web scraping, sensors, etc.). Ensure that the data is representative of the problem domain.

Data Preprocessing: Clean the data by handling missing values, duplicates, and outliers. Normalize or scale numerical features and encode categorical variables appropriately.

Data Splitting: Split the dataset into training, validation, and testing subsets. This ensures that your model is trained effectively and evaluated on unseen data.

Why it matters: High-quality data is the cornerstone of any AI model. Properly preprocessed data allows the AI system to learn more efficiently and make accurate predictions.

3. Choosing the Right AI Model and Algorithm

Once the data is prepared, the next step is selecting the appropriate AI model and algorithm for the task. Different AI techniques, such as machine learning (ML), deep learning, natural language processing (NLP), and computer vision, can be used depending on the problem at hand.

Key Activities:

Model Selection: Choose an AI model based on the problem type (e.g., decision trees for classification, neural networks for image processing, etc.).

Algorithm Choice: Choose an algorithm that works best for your selected model. Common algorithms include decision trees, random forests, support vector machines (SVM), k-nearest neighbors (KNN), and deep learning techniques such as convolutional neural networks (CNN) or recurrent neural networks (RNN).

Prototype Building: Before finalizing your model, it's often helpful to build a simple prototype to evaluate its performance and determine if it’s suitable for the task.

Why it matters: The choice of model and algorithm directly affects the accuracy and efficiency of your AI system. Testing different models helps ensure you select the one best suited to your needs.

4. Training the Model

Training is where the magic happens. During this step, the AI model learns from the data. Training involves feeding the data into the model and adjusting its parameters to minimize errors in predictions or classifications.

Key Activities:

Model Training: Use the training dataset to allow the model to learn patterns in the data. For supervised learning, this involves training on labeled data to learn the relationship between inputs and outputs.

Hyperparameter Tuning: Fine-tune the hyperparameters (e.g., learning rate, number of layers in neural networks) to optimize the model’s performance.

Cross-Validation: Implement k-fold cross-validation to ensure that your model generalizes well and avoids overfitting to the training data.

Why it matters: A properly trained model is essential for making accurate predictions or decisions. Training is an iterative process that involves refining the model to achieve the best results.

5. Evaluating Model Performance

After training, the next step is evaluating the performance of the model. This helps you understand how well the model generalizes to unseen data and how effective it is at solving the problem.

Key Activities:

Evaluation Metrics: Choose appropriate evaluation metrics based on the problem type. Common metrics include accuracy, precision, recall, F1 score (for classification problems), mean squared error (for regression), and area under the curve (AUC) for binary classification.

Testing on Unseen Data: Use the test dataset to evaluate the model’s performance. This provides an unbiased estimate of how well the model will perform in real-world situations.

Error Analysis: Analyze the errors the model makes to understand why they occurred and identify areas for improvement.

Why it matters: Evaluating the model’s performance helps ensure that it will meet the business requirements and objectives defined at the outset.

6. Model Optimization and Fine-Tuning

Once you have an initial version of the AI model, it’s time to optimize it for better accuracy and efficiency. Model optimization is the process of tweaking the model’s parameters to achieve the best performance.

Key Activities:

Feature Engineering: Add or remove features to improve the model’s learning capacity. Feature selection or extraction can help reduce overfitting and improve generalization.

Ensemble Methods: Combine multiple models (e.g., bagging or boosting) to improve predictive performance.

Model Compression: For large-scale models, techniques like pruning or quantization can reduce model size and improve inference speed.

Why it matters: Optimization ensures that the model is not only accurate but also efficient enough to handle real-world use cases at scale.

7. Deployment and Integration

The final stage in AI software development is deploying the trained AI model into production. This involves integrating the AI system into the larger software infrastructure and ensuring it operates as intended.

Key Activities:

Deployment Pipeline: Set up continuous integration and continuous deployment (CI/CD) pipelines to automate the deployment process.

API Integration: Develop APIs to allow other systems or applications to interact with the AI model.

Monitoring and Maintenance: Monitor the performance of the deployed AI system to ensure it continues to function correctly. Set up logging and alerting systems to detect any issues. Periodically retrain the model with new data to keep it relevant.

Why it matters: Deploying the AI model into production allows the end-users to benefit from the system. Ongoing monitoring ensures that the AI system remains effective and improves over time.

8. Feedback Loop and Iteration

AI development doesn’t end with deployment. In many cases, AI systems require iterative improvements based on real-world feedback. The feedback loop allows developers to collect user input, evaluate the system's performance in production, and make necessary adjustments.

Key Activities:

User Feedback: Collect feedback from users to identify potential issues, new features, or areas of improvement.

Model Retraining: Continuously retrain the model with new data and update it to improve its predictions and performance.

Continuous Improvement: AI models often require ongoing adjustments and improvements to handle evolving data and changing user needs.

Why it matters: AI software development is an ongoing process. Constant feedback and iteration are essential for improving the AI system and ensuring it continues to meet user expectations.

Conclusion

Building AI software from concept to code is a dynamic and iterative process. It requires a deep understanding of both the problem at hand and the tools available to address it. By following the step-by-step approach outlined in this blog, you can develop AI systems that are robust, scalable, and effective in solving real-world challenges.

From identifying the problem to deploying the model and iterating based on user feedback, AI software development involves continuous learning and refinement. As AI continues to evolve, staying up-to-date with the latest advancements and best practices will help you build AI solutions that drive innovation and deliver tangible value to users and businesses alike.

[blogbyahad]

How Quantum Algorithms Revolutionize Financial Portfolio Optimization for Risk Management

In the fast-paced world of finance, portfolio optimization is a critical component of risk management. Traditional methods often struggle to handle the complexities and vast datasets involved, leading to suboptimal decision-making. However, quantum algorithms are emerging as a powerful alternative, offering new avenues for enhancing financial portfolio optimization. Let’s explore how these algorithms revolutionize risk management in finance.

Understanding Portfolio Optimization

Portfolio optimization involves selecting the best mix of assets to maximize returns while minimizing risk. Key challenges include:

Complex Calculations: Evaluating potential asset combinations requires significant computational resources, especially as the number of assets increases.

Dynamic Market Conditions: Financial markets are volatile and influenced by numerous unpredictable factors, making it essential to adapt quickly.

Nonlinear Relationships: Asset correlations can be complex and nonlinear, complicating risk assessment.

Advantages of Quantum Algorithms

Increased Computational Power:

Exponential Speedup: Quantum algorithms can perform complex calculations much faster than classical computers. For example, using Grover’s algorithm, the search for optimal asset combinations can be accelerated, enabling quicker decision-making.

Simultaneous Processing: Quantum systems can analyze multiple potential portfolios at once, significantly reducing the time required for evaluations.

2. Improved Risk Assessment:

Advanced Models: Quantum algorithms can incorporate advanced mathematical models that better capture the nuances of financial data, leading to more accurate risk assessments.

Enhanced Simulations: Quantum Monte Carlo methods can simulate market scenarios with greater efficiency, allowing for more thorough stress testing and scenario analysis.

3. Complex Optimization Techniques:

Quantum Approximate Optimization Algorithm (QAOA): This algorithm is specifically designed for combinatorial optimization problems, such as selecting the best portfolio. It helps find optimal asset allocations by exploring various combinations more efficiently.

Quantum Machine Learning: Integrating quantum machine learning techniques can improve predictive analytics, identifying trends and patterns that inform better investment strategies.

Practical Applications in Finance

Dynamic Asset Allocation: Quantum algorithms enable real-time adjustments to portfolio allocations based on market changes, enhancing responsiveness to volatility and risk.

Risk Diversification: By analyzing complex relationships between assets, quantum algorithms can optimize diversification strategies, reducing overall portfolio risk.

Algorithmic Trading: Quantum-enhanced trading algorithms can quickly identify and exploit arbitrage opportunities, optimizing execution strategies while managing risk.

Case Studies and Real-World Implementations

Hedge Funds and Asset Managers: Several firms are exploring quantum computing for portfolio optimization, utilizing quantum algorithms to enhance their risk management strategies and gain competitive advantages.

Financial Institutions: Major banks are investigating the integration of quantum computing to improve their risk assessment models and portfolio optimization processes.

Challenges and Considerations

While the potential of quantum algorithms in portfolio optimization is significant, several challenges remain:

Technology Readiness: Quantum computing is still developing, and many financial institutions may not have access to the necessary hardware or expertise.

Data Security: As quantum computing advances, concerns about data security and privacy also rise, necessitating robust protective measures.

Integration with Existing Systems: Implementing quantum algorithms within traditional financial systems requires careful planning and technical knowledge.

Conclusion

Quantum algorithms are set to revolutionize financial portfolio optimization and risk management. By harnessing the power of quantum computing, financial professionals can enhance their ability to assess risk, optimize asset allocations, and respond rapidly to market changes. As the technology matures, those who embrace quantum innovations will likely gain a competitive edge in the ever-evolving financial landscape, paving the way for more informed, effective investment strategies.

[mathematicallybrunette]

I think it would work well for online courses. You’re teaching yourself so your success depends on your understanding. If you have context, your mind will connect the dots in the correct direction. Most full course vids for calc or lin alg or diff eq are between 6 and 11 hours so you would have to intentionally create time for them, but they are great resources.

[kwaamfan]

April 2024 update: the following list is no longer being maintained. please view my neocities site to view the resources i would currently recommend to people who are interested in learning thai. there’s fewer resources listed but i used everything there when i was starting out and can vouch for their quality, and i think it is more useful to beginners who may feel a bit lost or overwhelmed looking at the following list.

Under the read more is a huuuuuuuge (70+) list of free resources I’ve compiled during my time studying Thai, with some resources on Isaan and Lao as well. I’ve organized it by alphabetical order for Tumblr but you can view by level, format, and content on Notion (you don’t need an account to view btw). Since I’ve been using Notion to organize and keep track of all these resources that’s also where you’ll find more notes and future updates. This list focuses on resources meant specifically for language learners and does not include native content made for native speakers.

101 languages - 100 different vocab lists, mainly presented in full phrases. Link also includes audio download, good for Anki flashcards.

Aakanee - Uses their own illustrations and has native speakers describe what’s happening in them, as well as native speakers telling stories. Recordings include transcripts. They also have Isaan and Khmer learning materials.

Active Thai - Interactive website that teaches Thai script by breaking down the alphabet into consonants, vowels, and tones that are taught in chunks.

Advanced Thai with Kruu Momm - YouTube channel for intermediate/advanced level immersion videos. A teacher on Comprehensible Thai as well.

ALG World - YouTube channel for recordings of AUA sessions. Uses Dr. J. Marvin Brown‘s Automatic Language Growth method (basically immersion/comprehensible input) to teach Thai.

AUR Thai Online - YouTube channel for immersion-based lessons.

Banana Thai - Her YouTube has lots of reading and writing help, but also short themed lessons and a podcast. She also has a website with paid courses.

Benjawan Poomsan Becker books

Thai for Beginners, Intermediate, Advanced Audio and Vocabulary (also has links to Memrise courses with the vocab/audio)

YouTube playlists with audio for all books except Thai for Beginners

You can also find the accompanying audio for her books on Spotify, Apple Music, and Napster

Thai for Beginners

Thai for Intermediate Learners

Improving Your Thai Pronunciation

Speak Like a Thai, Vol. 1: Contemporary Thai Expressions

Speak Like a Thai, Vol. 2: Thai Slang and Idioms

Clozemaster - Gamified cloze sentences to acquire language through exposure to vocabulary in context.

Colloquial Thai: The Complete Course for Beginners - .pdf, audio files. Very little Thai script, almost all transliterated.

Comprehensible Thai - Largely English free YouTube channel that designs comprehensible input material for beginner and intermediate Thai students.

CU Intensive Thai Audio - Audio files for Chulalongkorn University’s Intensive Thai courses. I use these files for listening comprehension practice.

Everyday Thai - Includes three levels of basic lesson plans with games, quizzes, and flashcards. Also has recorded conversations with transcriptions for listening practice, songs, and additional reading exercises.

ExpatDen -  Basically a blog aimed towards expats or people who want to be one, but hosts lots of information on language learning. Collection of my favorite blog posts:

Master post of free resources

List of all free downloads related to learning Thai

Women Learn Thai master post

List of Thai-English readers

Thai language cheat sheets

Connectors (with Thai, English, and audio download): starter pack, opening, filler

Tense (with Thai, English, and audio download): part 1, part 2

Thai cat cartoons transcripts

Forvo - Hear native speakers pronounce words. Can download audio (great for building Anki decks).

Free Lao Books - Free pdfs of children’s books in Lao and English to practice reading.

FSI Everyday Lao - Basically a beginner textbook with audio on the side.

Fundamentals of the Thai Language - Textbook of lessons in an online format. Dry but more extensive than most lesson plans. Has a number of helpful appendices (including idioms, family relations, cooking terms, etc.)

Glossika Mass Sentences: Thai Fluency -  Basically a bunch of example sentences, with the difficulty increasing across books. Unfortunately I haven’t found the audio for these books so better used as supplementary reading practice. Uses IPA transliterations.

Fluency 1

Fluency 2

Fluency 3

I Love Languages - Lessons are much vocab lists, with example phrases utilizing them. Mainly useful for its grammar section, which goes over adjectives, imperatives, pronouns, prepositions, etc.

Isaan Dialect | Siamsmile - Some background on the Isaan dialect, general differences between Thai and Isaan, and a short vocab list.

Isaan Language - In depth discussion on the phonological differences between Thai and Isaan. Has some vocabulary and grammar info too.

Khruu Peter - Teacher from AUA vlogs about daily life in Thailand, good for intermediate listening comprehension.

Langhub - Lots of lessons. Includes basic beginner/intermediate/advanced tiers as well as more tailored lessons (lessons for partying, university, the legal system, etc.).

Language Hut School - Very short videos (~2 minutes) by native Thai speakers teaching small grammar lessons, related phrases, etc.

Learn Thai Ping - Website that teaches you how to type in Thai. Lessons are broken down by phonetics.

Learn Thai Thaigomaster - Mainly advertises their Chiang Mai language learning school but has a good playlist on Thai basics (especially for grammar), some short clips sorted by each instructor at their school (I like to use for beginner level listening practice), and lessons meant to go with their book (which is pretty cheap).

Learn Thai with BoBo -  Vocab lists with audio at native and slow speed. Audio is easy to download and has Thai, English, and transliterated text - great source for Anki flashcards. She also has a YouTube channel where she covers topic specific vocab by presenting full sentences and breaking them down word by word.

Learn Thai with Shelby - Mostly short, weekly videos. Has stuff on Isaan, intermediate/advanced topics, love and relationships, culture.

Learning Thai with Bangkok Post - Bangkok Post articles with audio, Thai transcript, and English translation. Some key vocabulary from the article is presented after the Thai transcript and before the English translation; the audio also goes aver the vocabulary.

Lingo Hut - Has a lot of short lessons. Each lesson is basically a list of vocab, and they have games to help memorize them (flashcards, tic-tac-toe, concentration, listening games).

Lingopolo - Themed lessons. You can choose recommended lessons or pick whatever you want to learn. Recommends lessons based on previously known words and phrases. Audio based; pretty much presents flashcards and then quizzes you on them. After each “card” you can see how the word is used in example sentences, or see each word used if the card was a sentence/phrase.

Maanii Readers - Website where you can download the Maanii books as pdfs and audio of a native speaker reading them. You can also view each lesson in each book as interactive webpages (listen line by line, hover over words to view their English translation).

Mango Languages -  Conversation based lesson plans. Learn by building new sentences through given vocabulary. Also available as a mobile app. Paid but free through my local library. Check if it’s available near you here.

Memrise - Kinda like an online Anki but more modern UI with user-created flashcards. They have an app but I think you have to add courses on their desktop site first.

Pablo Roman - Has a playlist of recordings in Thai from aakanee narrating daily activities and routines. All videos link to the corresponding aakanee transcript.

Pick Up Thai -  Produces paid podcasts and books geared towards immersion (with some free samples), but they also have free blog posts explaining slang or other finer points of the language, as well as really cute wallpaper dictionaries. I like their page on translations of Thai memes and their listening comprehension page (includes transcriptions).

Picture dictionaries

Thai Picture Dictionary by Jintana Rattanakhemakorn

Thai Visual Dictionary by Collins Dictionaries

Read Thai in 10 Days - Best resource for learning how to read Thai in my opinion. azw3 (Kindle format), audio.

Riam Thai - Immersion-based lessons including beginner videos. A teacher on Comprehensible Thai as well.

SEAsite Lao - Comprehensive website full of lessons, vocab, grammar notes, reading and listening exercises, and cultural info on Laos.

SEAsite Thai - Very similar to SEAsite Lao. Old af website so not everything works, but a lot of the resources are still up. I mainly use this website to find sentences in Thai with audio for Anki flashcards.

Self Study Thai - Translations of articles with audio; has audio by paragraph or by line.

Slice of Thai - This website has a variety of information on Thailand including their food and their culture, but also has a great language section. It focuses on the sounds of the language, especially parts that native English speakers have trouble hearing through the use of spectrographs.

Speak Thai Easy - Mostly short videos giving tips, grammar explanations, and vocab. I really like her grammar videos.

Speak Thai Possible - Short clips meant to provide tips and improve pronunciation. Good resource for learning and understanding spoken, colloquial Thai.

Spoken World: Thai - Beginner book for self studying Thai. While transliterations are always provided, in my experience this book is way more effective if you learn how to read before using it. pdf, audio.

Study Thai Subs - Thai sentences and phrases from movies with the audio of the line and the English translation. Can be from original Thai movies or from Western movies dubbed into Thai.

Thai 2 English - Thai-English dictionary. Nice UI; includes example sentences as well as compound words or phrases a given term is used in. Gives the different meanings of a word, frequency of its use, and an explanation if the word is not directly translatable.

Thai Conversation Café - Mainly immersion videos; lots of food and daily life. Has some videos on reading and writing. A teacher on Comprehensible Thai as well.

Thai Growth Expert - Immersion based videos mainly teaching phrases; has content on improving pronunciation as well. A teacher on Comprehensible Thai as well.

Thai Language and Culture for Beginners

Book 1 (djvu)

Book 2 (djvu)

supplementary audiovisuals

Interactive website (can be glitchy)

YouTube

Download

Thai language | Omniglot - Basically gives an overview of the Thai language and script. Mainly useful for the plethora of links to actual language learning resources at the bottom.

Thai Lessons with New - Tons of playlists on vocabulary, grammar, speaking like a Thai/words in context, etc. I really like her grammar playlist. Puts Thai, transliteration, and English in the description.

Thai Notes - Has a reading/script course as well as lessons based on the Foreign Language Service Thai Language Course. Only the reading course has integrated interactive games/quizzes. Has some cool tools like a Thai typing trainer and a classifier finder, as well as some reading exercises.

Thai Reference Grammar - Book with lots of example sentences illustrating many different grammar structures. More extensive than the Smyth Essential Grammar book. pdf.

Thai With Grace -  Podcast for beginners. Also has a YouTube channel that covers basic lessons and vlogs in Thai with English and Thai subtitles to practice listening and immersion.

Thai with Mod -  YouTube channel mostly with short clips giving phrases used in a specific context (talking about COVID, ordering food, asking someone out, etc.)

thai-language - Best dictionary site. Has 70,000+ dictionary entries, 20,000+ audio clips, lessons, reference pages, and tons of reading exercises. Isaan words can be found here.

Thai: An Essential Grammar - Concise and simple book on Thai grammar. Beginner friendly and good reference material but I don’t like that the transliteration is emphasized more than the Thai script. epub.

ThaiPod101 -  Most lessons and features on their website require a subscription, but free users still have access to lots of vocab lists and pretty cheat sheets. Vocab lists come with audio for both words and example sentences, making it easy to make Anki flashcards from them, and you can hide romanization. They also have a YouTube channel with lots of high quality videos going over everything from consonants, conversation based listening practice, and vocab related to culture.

Transparent Language - Lessons basically introduces vocab and phrases then tests you on it. Uses a variety of games and exercises to help memorize. Paid but free through my local library. Check if yours carries it here (in US and Canada).

Understanding Thai - Former AUA teacher who focus on immersion/comprehensible input. Also has videos on slang. A teacher on Comprehensible Thai as well.

[rigelmejo]

Updated 6/8/2025 - List of Comprehensible Input Chinese Resources:

Comprehensible Input Wiki - this wiki includes tons of Comprehensible Input Lessons linked for many languages. I go back to this regularly. Go to the Chinese sections for Chinese.

Vidioma.com - a person made this site to make it easy and convienient for people learning Chinese to find CI Lessons for their level of understanding. I think they were trying to make something similar to Dreaming Spanish's site to help encourage learners to start/continue by making it easy and in one place. Time watched is tracked on the local device you're using it on, there's no account sign up, and the website makes no money - it links youtube videos of youtubers that teach Chinese.

r/ALGMandarin Wiki - includes playlists made by learners of the content, sorted for beginners.

r/ALGhub Aural Resources List - includes comprehensible input lessons and learner podcasts for many languages, go to Chinese - Mandarin section.

Lazychinese.com - Su Qing made this website, her youtube channel is Lazy Chinese. Like Dreaming Spanish, it is Comprehensible Input Lessons on a website where paying a subscription will unlock more lessons. This website is still growing, the payment goes directly to Lazy Chinese and the teachers making the lessons. (As it is still growing, I recommend also checking out each teacher's youtube channels too, for example I love Xiaogua Chinese channel).

r/ALGhub What Is Automatic Language Growth? - page that explains ALG if you want to to it. (My quick summary is ALG is using only comprehensible input lessons that contain ONLY the target language, until you can use materials for native speakers, avoiding thinking about the language such as anaylzing/translating in your head/using translations and explanations, and waiting to speak and read until you feel you have a good grasp of listening skills. So 600-2000 hours depending on the language, ALG Thai courses typically recommend waiting 1000-2000 hours, Dreaming Spanish typically recommends waiting 600-1000 hours. Note: ALG is stricter than Krashen's input hypothesis that "we acquire language by having meaningful experiences we understand in the language" and therefore CI is not a synonym for ALG. ALG is comprehensible input, but comprehensible input is a much BROADER category than ALG. ALG was invented by Marvin Brown, who felt it is ONLY comprehensible experiences in the language we acquire language from, and nothing else is necessary or beneficial. Brown felt the other activities were detrimental to success. Brown also felt speaking early, or any explicit study and analysis of ANY language would damage ultimate ability in languages. This is the controversial point - as many other teaching programs that include Comprehensible Input Lessons still feel there's a place for grammar study and translations and explanations. Most learning programs for learning a language, do not worry that explicit study will damage their ultimate result, and do not care when one begins to read or speak).

Dreaming Spanish Method - includes the roadmap I'm often referencing, Dreaming Spanish Method is the ALG method, just a bit more lax. Dreaming Spanish also says to avoid explanations and translations, but to look you at them if curious then it won't hurt. Dreaming Spanish says you should wait to read and speak 600-1000 hours, but if you need to do it earlier then do, or if you will give up unless you do them early then just do them. (This is basically why I prefer going to r/dreamingspanish, their more lax approach to the ALG method means I can find more learners who are using Comprehensible Input Lessons alongside other study activities or study history, which is more compatible with my own experiences).

*personal note: think ALG's ideas are a bit extreme. I do not think explicit study, translations, speaking early, or reading early will create an insurmountable block for most people's language goals. I am not doing pure ALG. If you feel like doing pure ALG though, it will work. There's plentiful examples on r/dreamingspanish of people doing pure ALG to successfully reach B2 level, and people doing additional things that contradict ALG and successfully reaching B2 level. Dreaming Spanish's method and roadmap are a slightly more lax approach to ALG if you'd like to try it out without completely following the ALG rules, and you can find many people to connect with who also did ALG somewhat but not purist in that learning community.

My recommendations are: no matter who you are, the linked resources above are ALL useful for Practicing Extensive Listening. You'll need to practice listening to improve your listening skills, and many of these resources will have easier options for beginners and intermediate learners to practice with. These linked resources also are great ways to learn words/grammar in visual context with no translations, and learning more is always useful. If you enjoy learning from context, you may find these resources suit how you like to learn. So I think anyone studying could find these useful.

[boburnhamhistorian]

Hi, everyone!

BIG news on the YouTube front—Welcome to the Internet just hit 99 MILLION views today! 🥳

In other news, I was reading about the Ennui Engine, and this author must have seen Inside or just agrees with Bo about the IV drip of mediocre content that is slowly ruining our lives.

We scroll through Twitter, Facebook, TikTok, and Reddit, vaguely hoping to find something with which to amuse or inform ourselves before getting up in the morning or going to bed at night. We favor videos that either are very short or don’t require dedicated focus, confident in the knowledge that we can move on to something else whenever we want to. We ignore thoughtfully composed “walls of text,” but we electronically applaud memetic image macros and single-sentence references that aren’t inherently entertaining or insightful (yet are somehow still poorly written). When we amplify these things – using our likes, upvotes, retweets, and shares – we encourage the creation of more low-effort content, and in so doing, we send the message that higher-quality offerings are unwelcome and unwanted.

Even when “difficult” pieces of content do get seen, they still share the stage with everything else, marking them as being no better than equal to things that require minimal care and effort to create and consume.

Therein lies the real problem, however: We don’t enjoy the low-effort content… at least not as much as we’ve tricked ourselves into thinking that we do.

Really thought-provoking and well-written article, and it makes me rethink my entire relationship with the Internet—what exactly DO I get out of scrolling for hours on end? Sigh

All we can do is view everything online critically and with a grain of salt. As the author optimistically concludes, we CAN make things better:

The Ennui Engine keeps roaring, and we’re left with tiny, stale pellets that we tell ourselves are satisfying. Beneath the lie, though, we only feel depressed, disconnected, and frustrated.

There is a solution to all of this; a way that we can reclaim our lives, help both people and online entertainment improve, and escape the endless churn of the Ennui Engine. It doesn’t begin with turning to legislators or forum-administrators, though, and it doesn’t involve a retreat from the Web, but it does require that we stop encouraging the ritual. As unpleasant as it may be to admit, we are each individually to blame for this slump-inducing cycle’s persistence, and we are each responsible for halting it.

Whenever we feel ourselves getting listless, we should step away, then challenge ourselves to find (or create) something new, original, and requiring of a bit more effort than we might initially want to expend. We need to remember that five minutes invested in reading an article – even a mediocre one – will almost always offer a better payout of emotional energy than five minutes of gambling on a slot machine with only one reel.

The Internet was created with the intention of connecting exceptional people and sharing noteworthy content, and it can still fulfill that purpose today. As such, the takeaway here is not that we should distance ourselves from social media, turn off our screens, or reject the trappings of the modern era. Instead, we should remain self-aware and discerning as we traverse the Web, encouraging, applauding, and insisting on effort and earnestness from anyone who intends to contribute (no matter how small or substantial their contributions might be). The Ennui Engine will continue running, of course, but we can each make the personal choice to keep from sacrificing ourselves to it… and we can warn others against getting ground up in its gears.

I was also reading about how Google offered its suite of software for free—including YouTube videos as educational resources—to schools, planning on getting young children addicted to the algorithm (only benefitting the bug-eyed salamanders, indeed).

I just try to keep my kids informed and discerning about what content they are consuming (no easy task, but I think I made a breakthrough when my 11yo daughter got my point about how no massively popular Roblox YTers exist who are female AND American without an insane, ultra-feminine schtick...why is that?)

Hope you all are doing well, and I have lots more SUBSTANTIAL posts coming up (more interviews, analysis of Bill Bailey and Bo, plus my own curated IV drip of artwork for February...I did the mindless scrolling so you don't have to! Haha) ✌🏼

[tasteleeknow]

hiii, i run a page 'k-bookclub' that promotes the idea of giving authors feedback, I'm looking to put together resources on how to support authors on tumblr and I've seen your post about how to reblog come up on my feed a few times, would it be ok for me to link that post on my page? algs if not but thought I better ask first, thank you !

yeah that's all good, sound cool

[rubiks-cube-cheat-sheet-ee]

rubiks cube cheat sheet working W9M0+

💾 ►►► DOWNLOAD FILE 🔥🔥🔥🔥🔥 Collection of algorithms on how to solve the Rubik's cube presented as digital cheat sheet tutorials and speed solving resources. Best free website and app. We divide the Rubik's Cube into 7 layers and solve each group not messing up the solved pieces. how to solve the rubiks cube cheat sheet. Check out this airtight Rubik's Cube cheat sheet Simple Life Hacks, Simple Tricks, Aesthetic. 25k followers. More information. Rubik's Cube Cheat Sheet (Solution #1) · Step 1 -- Do the first face · Step 2 -- Do the middle layer edge pieces · Step 3 -- Form cross on last layer · Step 4 9 Desktop users can install this web app as a Google Chrome application for a better, faster and offline experience. Google Chrome and Safari offers the best browsing experience on most devices. The purpose of this web app is to collect essential and useful resources any "beginner" speed cuber needs in a single location. I initially kept track of algorithms that my kids and I learned or wish to learn. Know that there are many other good algorithms out there that can work better for you. I try to point you to those resources as best as I can across the app. I wanted the content to first, be optimized for all devices desktop, mobile, android, apple ios iphone and ipad and second, accessible offline so that we can get rid of messy paper cheat sheets! This app is my attempt to efficiently fit as many algorithms as possible in one screen for any devices on the go and small contribution to help the community grow. I will keep adding features and algorithms to this app over time. If you think this app is useful please share it with your friends! You can donate through PayPal using the button below. Your support is greatly appreciated! A change log will be maintained here and on this Facebook page. Dan's Cubing. Pro Tip: Interact with Algorithms Sometimes, having a different perspective or visual cues can really be handy. Click or tap any case image to view variations of the algorithm. Click or tap any algorithm sequence to visualize the steps on a virtual cube on alg. Tap the "Add to Home Screen" action. Option 1 : Open your browser "Options" menu in Google Chrome. Option 2 : Chrome will automatically show an install icon in the address bar. Just click on it to install. Website Launch October 31, Terms of Use - Privacy Policy. Hand Crafted by Daniel Racine. All Rights Reserved.

[howelljenkins]

hey to standardized test anon:

r/strugglebuddies has a mega drive full of old ap/sat tests and resources (ie barron book pdfs and etc) this is the google doc https://docs.google.com/document/d/1dTGFVKQBjk_KJn2J04okCxXm-SqTy01UlS0X_zwPNhs/edit that has the mega drive link along w the access key, but it usually goes down every few months so download what u need, but also https://www.cracksat.net/index.html also these problem sets for calc are really good and they have the answer keys with explanation: https://www.math.ucdavis.edu/~kouba/ProblemsList.html and professor leonard teaches calc and alg/prealg/statistics really well too this has study guides for diff subjects too: https://www.studyshed.org/ also r/a2c is good for resources to apply to college but it's so easy to spiral down there..... and the people on there can be super super jank

anyways, good luck! hope this helps!

^

[acadernia]

HI JAS!! how are you doing lately?

HI!!!! and happy new year— break has passed by so quickly and i have been completely unproductive (mostly as planned??) ! school got pushed back a week and we'll be going remote for two weeks as well— hope everyone's staying safe!

reading-wise, i wrapped up mindwise by nicholas epley and writers and lovers by lily king. loved the first, thought the latter was okay ?¿ i also wrapped up some 2021 writing pieces, which i'm super happy about, because i've had a bit of a creative block for the past couple of months. otherwise, i've spent the past couple of weeks getting super into stardew valley and settlers of catan, haha

i never got around to making an update post on the past quarter, but it was the busiest i've ever been in my life (got pretty burnt out by the end)— took proof-based lin alg, analysis, python, and econ for classes, and started work as a research assistant for a social psych lab + teaching assistant for calc, both of which have been pretty rewarding experiences. that being said, I don't think I ever want to commit to that much ever again— pretty brutal quarter overall.

so! some goals for the new year: I'd like to continue research + teaching, participate in escapril again, make more time to be with friends + write/draw/read. my reading goal this year is 20 books (last year was 25— too difficult T_T). and i'd like to commit more to this blog, even if i'm not taking photos — i've never really done misc. update posts because i don't think they'd be interesting to others, but at the same time, i did make this blog to track my own progress / work as a sort of visual journal for me, and so i don't want to lose track of that either ?¿ not sure! i'll figure it out LMAO . I do think I'm at the point in my college career where I might be able to put together helpful guides / resources, so looking at that as well (stuff like reaching out to professors, putting together 4-year plans, getting involved in research, etc)!! :)

anyways— lots of rambling— but thanks for checking in and i hope you are safe & well!! have a wonderful new year and here's to a great 2022 :)<3

[sevenfactorial]

Hi! Can you tell some uni or colleges math resources?

Can you be more specific? Like resources for studying for particular undergrad level classes?

A few “classic” online references:

Paul’s online math notes (https://tutorial.math.lamar.edu/): algebra, calc 1-3, diff eqs though I’ve mostly only used the calc ones. A common favorite

Khan Academy: haven’t actually used any of their math stuff for years but I remember their videos were good

3blue1brown: he has a series on calc, diff eqs, and linear alg. I haven’t actually watched many of these either but his videos are generally good and I know people who like the series in particular

If you mean higher level math, I tend to just use a search engine and end up referencing a mix of wikipedia, wolfram mathworld, random pdfs from various universities, and math stack exchange. And of course textbook pdfs

If you give me more details, I’ll see if I can think of anything else!