AI Tools & Frameworks Directory

Learn seven engineering techniques to train large language models on consumer GPUs without running out of memory.

In this article, you will learn how to build, track, compare, and register scikit-learn pipelines that integrate large language models using Scikit-LLM and MLflow. Topics...

How model validation standards are changing for LLM-based systems: what breaks, what carries over, and how to test output quality The post The Model Validation Playbook for GenAI: Lessons from Banking appeared first on Towards Data Science.

Over the past several years, I have worked through three successive generations of intelligent retrieval systems, each solving problems the previous generation could not. Here is what I have learned.

The way we build interfaces is changing. As AI agents write more of our code, the tools we use to render that code may need to change too.

Explore five free ways to access AI coding agents, proprietary coding models, and open-weight models without paying for expensive subscriptions or GPUs.

As LLM applications grow more complex, inference cost and latency become increasingly important. A single request can contain thousands or even millions of tokens from system instructions, conversation history, retrieved documents, tool definitions, and user input. Reprocessing the same information ...

A context window can be technically complete and still describe a world that no longer exists. I built a deterministic benchmark to measure the cost of acting on stale context. The post Context Windows Don’t Know What’s Still True — I Built a Validity Layer That Does appeared first on Towards Data S...

Last week, a GitHub notification arrived while I was asleep: a bug had been reproduced in staging, documented with screenshots, and assigned to the right engineer. A bot I set up four days earlier did the work overnight. That is the gap Grok Bot is designed to close. Instead of suggesting what to do...

AI companies quietly watermark billions of words a day. Here’s how to apply the same three families of techniques to your own writing—and what real experiments reveal about which watermarks survive copy-paste, editing, and paraphrasing. The post Text Watermarking in Python: Catch Whoever Copies Your...

Improving reinforcement learning for complex physics The post Dynamical System Transfer Learning with Reduced Order Models appeared first on Towards Data Science.

OpenAI has released GPT-6 Astra, its newest frontier model, less than a week after Anthropic’s Claude Fable 5.1. OpenAI calls Astra the world’s most intelligent and aligned model yet. What actually makes Astra different? The simplest way to put it is this: Astra is built to do more, not just answer ...

Stop sending every AI request to your most expensive model. See how intelligent routing can cut cost and latency without sacrificing much quality.

Explore five free AI API providers for accessing large language models, fast inference, multimodal AI, and agentic applications without paying for API usage.

Turning a trained churn classifier into a FastAPI service that other software can actually call. The post My Model Worked Perfectly. Then I Tried to Make It Useful. appeared first on Towards Data Science.

I built a prompt dependency graph that separates everything a component can reach from the smaller set that actually needs targeted evaluation. The post Changing One Prompt Can Affect 50 Others — I Built a Prompt Dependency Graph to Find What Needs Retesting appeared first on Towards Data Science.

A curated, linear pipeline of high-signal free resources that takes you from backpropagation basics to deploying production-grade LLM applications.

OpenCode is open source and works with any model, but those are no longer its most interesting features. Model choice is table stakes. What sets OpenCode apart is its architecture, and the trade-offs that come with it, especially if you are coming from Claude Code.  In this article, we look at what ...

Simply knowing that a 35-year-old male in Seattle clicked 12 times last month tells you almost nothing about his intent.

I built a matcher meant to finish the cleanup that normalization left behind. Testing it against real data showed that no version of it could be made safe. What follows is the architecture that was left once the matcher was set aside. The post Avoiding Entity Key Drift in a Data Lake: Step 2, When F...

Discover how FireDucks can speed up pandas workloads with lazy execution, compiler optimization, and multithreaded processing, delivering up to 20x faster DataFrame performance in our benchmark.

A visual guide to how graph neural networks work under the hood The post Graph Neural Networks: GCN, MPNN, and GAT, Explained Simply appeared first on Towards Data Science.

Deploy agentic AI across SRE, finance, legal, migration, and security with deterministic safety constraints.

In this article, you will learn how to design reliable memory systems for AI agents, covering both the patterns that work and the common architectural...