AI Tools & Frameworks Directory

PostgreSQL is fast. Whether your Python code can or should keep up depends on context. This article compares and benchmarks various insert strategies, focusing not on micro-benchmarks but on trade-offs between safety, abstraction, and throughput — and choosing the right tool for the job. The post Fa...

Large language models like LLaMA, Mistral, and Qwen have billions of parameters that demand a lot of memory and compute power.

This is an "expectations vs reality" approach to demystify, based on research of real success and failure stories, what are the capabilities and limits of vibe coding.

Why privacy breaks fairness at small scale—and how collaboration fixes both without sharing a single record The post I Evaluated Half a Million Credit Records with Federated Learning. Here’s What I Found appeared first on Towards Data Science.

Human-guided AI collaboration The post Probabilistic Multi-Variant Reasoning: Turning Fluent LLM Answers Into Weighted Options appeared first on Towards Data Science.

A list of ready to use n8n workflow templates that help data scientists quickly analyze data, extract and transform it, and build reliable knowledge bases.

Editor’s note: This article is a part of our series on visualizing the foundations of machine learning.

Learning Python at the beginning feels deceptively simple. You write a few lines, the code runs, and it’s tempting to think you’ve got it. Then you try to build something on your own and… nothing works!? Turns out all the information you had learnt, didn’t find an outlet.  That’s where challenging p...

This article is divided into four parts; they are: • The Reason for Fine-tuning a Model • Dataset for Fine-tuning • Fine-tuning Procedure • Other Fine-Tuning Techniques Once you train your decoder-only transformer model, you have a text generator.

Choosing a cloud services provider can feel a lot like dating: every vendor promises reliability, security, and support, but only a few truly live up to it. The wrong choice can lead to costly downtime, security headaches, or performance bottlenecks that ripple across your business.

A practical guide to observability, evaluations, and model comparisons The post Measuring What Matters with NeMo Agent Toolkit appeared first on Towards Data Science.

Build ML web apps in minutes with Gradio's Python framework. Create interactive demos for models with text, image, or audio inputs with no frontend skills needed. Deploy and share instantly.

Building data pipelines? These Python ETL tools will make your life easier.

Most ChatGPT users don't know this, but when the model searches the web for current information or runs Python code to analyze data, it's using tool calling.

Which of these state-of-the-art models writes the best code?

Long-running LLM applications degrade when context is unmanaged. Context engineering turns the context window into a deliberate, optimized resource. Learn more in this article.

Instead of using shift as an excuse for poor performance, use Inverse Probability Weighting to estimate how your model should perform in the new environment The post Stop Blaming the Data: A Better Way to Handle Covariance Shift appeared first on Towards Data Science.

Read these 7 tricks for treating your Docker container like a reproducible artifact, not a disposable wrapper.

A deep dive on data transfer bottlenecks, their identification, and their resolution with the help of NVIDIA Nsight™ Systems The post Optimizing Data Transfer in AI/ML Workloads appeared first on Towards Data Science.

Large AI models are scaling rapidly, with bigger architectures and longer training runs becoming the norm. As models grow, however, a fundamental training stability issue has remained unresolved. DeepSeek mHC directly addresses this problem by rethinking how residual connections behave at scale. Thi...

A prerequisite for long-term success of machine learning systems The post Drift Detection in Robust Machine Learning Systems appeared first on Towards Data Science.

Power BI is an influential tool, shaping raw data into informative visuals and reports. With a user-friendly interface and formidable functionalities, Power BI is an invaluable platform for individuals to refine their skills through hands-on projects. By engaging in Power BI practice projects, begin...

Liquid Foundation Models (LFM 2) define a new class of small language models designed to deliver strong reasoning and instruction-following capabilities directly on edge devices. Unlike large cloud-centric LLMs, LFM 2 focuses on efficiency, low latency, and memory awareness while still maintaining c...

How to build, score, and interpret RFM segments step by step The post EDA in Public (Part 3): RFM Analysis for Customer Segmentation in Pandas appeared first on Towards Data Science.