AI Tools & Frameworks Directory

Most real-world classification problems are imbalanced. Fraud, disease, churn, and defects are rare by nature. Standard classifiers chase accuracy, so they quietly ignore the very class you care about. For years, SMOTE was the reflex fix that everyone reached for first. But SMOTE often fails on the ...

LLMs don’t fail because they forget—they fail because they remember too much. As conversations grow, prompts accumulate redundant and low-value tokens, driving up cost and latency while silently degrading output quality. This article introduces a deterministic prompt-pruning layer that reduces token...

In this article, you will learn how to choose the right memory strategy for an AI agent by working through a simple decision tree, one...

Building a production-ready RSS pipeline with Python, Docker, PostgreSQL, and Kestra The post I Built My Second ETL Pipeline. This Time, I Started Thinking Like a Data Engineer appeared first on Towards Data Science.

A practical next step into partitions, shuffles, joins, caching, and execution plans. The post PySpark for Beginners: Building Intermediate-Level Skills appeared first on Towards Data Science.

You don't need a PhD to understand fine-tuning. This article explains how pretrained models learn new skills through fine-tuning.

SmolVLM2-2.2B sits at a genuinely useful point on the capability-size trade-off curve; small enough to run on a single consumer GPU, capable enough to produce video summaries that are actually useful for real workflows.

What our over-dependence on external consulting teaches us about delegating our minds to machines The post The Big Con of Agentic AI appeared first on Towards Data Science.

For twelve days, the best AI models on the planet existed and almost nobody could touch them. That ends now! GPT-5.6 Sol, Terra, and Luna go public today! The models are accessible by all users (no subscription required) This is the full breakdown of what’s on offer: three models, four prices, one p...

AI agents are moving from one-time assistants to persistent workers that can repeat tasks, monitor changes, run checks, update workflows, and return with results. Instead of prompting an LLM once and deciding every next step manually, teams can now use AI agents that keep working (on a Loop) until a...

This article covers the full path from zero to a running private research assistant on Telegram, including configuring the context length correctly, connecting the channel, enabling web search, and deploying it headlessly in Docker.

DeepSeek’s new DSpark module brings speculative decoding to DeepSeek-V4. It might look like a niche inference tweak, but in production it boosted per-user generation speed by 60 to 85 percent with no drop in model quality. What sets DSpark apart is that it tackles two longstanding problems at once, ...

Hint: it is not GPU speed! The post The Real Challenge Limiting AI Models Today appeared first on Towards Data Science.

Map AI value, design workflows, redefine talent, upgrade the executive team, and measure the business impact. The post Redesign Work Before You Add More AI Agents appeared first on Towards Data Science.

How to decide when an AI agent should act on its own by using cost asymmetry instead of a fixed confidence cutoff The post The Threshold Is a Price, Not a Percentage appeared first on Towards Data Science.

How should we ensemble time-series forecasts better? The post Information Theory and Ensemble Models appeared first on Towards Data Science.

The simplest most important idea for time series forecasting The post Measuring Structure Stability of Econometric Models appeared first on Towards Data Science.

A technical comparison of Proxy-Pointer and LLM-Wiki The post Proxy-Pointer RAG: Temporal Reasoning Without Semantic Precompilation appeared first on Towards Data Science.

A model is almost never 100% sure of anything. These 10 probability concepts explain how it makes decisions anyway.

Treating model degradation as a time-to-failure problem The post Survival Analysis for Data Drift and ML Reliability appeared first on Towards Data Science.

In June 2026, Google introduced the Open Knowledge Format (OKF), an open specification for how AI agents organise and exchange knowledge. An OKF bundle is just Markdown files, lightweight YAML metadata, and links between concepts, yet it challenges the assumption that every AI application needs embe...

The role is shifting from building models to managing them.

You describe the model. It writes the code, runs the training, and ships the checkpoint. Welcome to ML Intern.

This article looks at five concrete ways SLMs are showing up inside next-generation agents right now, from the research backing them to the tools and numbers worth knowing if you're deciding whether your next agent needs a frontier model at all