AI Tools & Frameworks Directory

Understanding the architecture, training pipeline and implementing TabPFN in practice The post Exploring TabPFN: A Foundation Model Built for Tabular Data appeared first on Towards Data Science.

Many AI systems focus on isolated tasks or simple prompt engineering. This approach allowed us to build interesting applications from a single prompt, but we are starting to hit a limit. Simple prompting falls short when we tackle complex AI tasks that require multiple stages or enterprise systems t...

Agent creation has become easier than ever but have you ever thought – how can we make them more powerful than they already are? I recently thought of one possible way – what if they had realtime information about specific categories like finance and movies. That would be really cool, right? While e...

The NotebookLM is a relatively new Internet phenomenon, in which Google has distinguished itself, thanks to its Audio Overview mode – a mechanism that transforms the text in the paper into a two-person podcast. All of this, in a single click. But what should you do when you wish to build it yourself...

This article is divided into two parts; they are: • Data Parallelism • Distributed Data Parallelism If you have multiple GPUs, you can combine them to operate as a single GPU with greater memory capacity.

This article is divided into two parts; they are: • Using `torch.

An intuitive explanation of transforming random variables correctly. The post Keeping Probabilities Honest: The Jacobian Adjustment appeared first on Towards Data Science.

An intuitive, step-by-step look at how Transformers use self-attention to turn static word embeddings into contextual representations, illustrated with simple examples and an Excel-friendly walkthrough. The post The Machine Learning “Advent Calendar” Day 24: Transformers for Text in Excel appeared f...

This article is divided into three parts; they are: • Floating-point Numbers • Automatic Mixed Precision Training • Gradient Checkpointing Let's get started! The default data type in PyTorch is the IEEE 754 32-bit floating-point format, also known as single precision.

If you have an interest in agentic coding, there's a pretty good chance you've heard of <a href="https://jules.

How cyclical encoding improves machine learning prediction The post Is Your Model Time-Blind? The Case for Cyclical Feature Encoding appeared first on Towards Data Science.

Best OCR and vision language models you can run locally that transform documents, tables, and diagrams into flawless markdown copies with benchmark-crushing accuracy.

A step-by-step 1D CNN for text, built in Excel, where every filter, weight, and decision is fully visible. The post The Machine Learning “Advent Calendar” Day 23: CNN in Excel appeared first on Towards Data Science.

This article is divided into two parts; they are: • What Is Perplexity and How to Compute It • Evaluate the Perplexity of a Language Model with HellaSwag Dataset Perplexity is a measure of how well a language model predicts a sample of text.

Understanding the process behind agentic planning and task management in LangChain The post How Agents Plan Tasks with To-Do Lists appeared first on Towards Data Science.

A data scientist's guide to population stability index (PSI) The post Stop Retraining Blindly: Use PSI to Build a Smarter Monitoring Pipeline appeared first on Towards Data Science.

Coding experts tend to use 30-40% of their time only for comprehending the already existing code. These are two entire working days every week that are wasted on going through obsolete documentation, understanding ambiguous code, and desperately searching for developers who quit months ago.  On the ...

A brief overview of the math behind the Harsanyi Dividend and a real-world application in Streamlit The post Synergy in Clicks: Harsanyi Dividends for E-Commerce appeared first on Towards Data Science.

Understanding text embeddings through simple models and Excel The post The Machine Learning “Advent Calendar” Day 22: Embeddings in Excel appeared first on Towards Data Science.

For the last couple of years, a lot of the conversation around AI has revolved around a single, deceptively simple question: Which model is the best? But the next question was always, the best for what?  The best for reasoning? Writing? Coding? Or maybe it’s the best for images, audio, or video? Tha...

This is a list of top LLM and VLMs that are fast, smart, and small enough to run locally on devices as small as a Raspberry Pi or even a smart fridge.

How to make LLMs reason with verifiable, step-by-step logic (Part 1) The post Understanding Vibe Proving appeared first on Towards Data Science.

An LLM that's 41× more efficient and 9× faster than today's standard models The post What Happens When You Build an LLM Using Only 1s and 0s appeared first on Towards Data Science.

MCP is a key enabler into turning your LLM into an agent by providing it with tools to retrieve real-time information or perform actions. In this deep dive we cover how MCP works, when to use it, and what to watch out for. The post Tools for Your LLM: a Deep Dive into MCP appeared first on Towards D...