📰 Towards Data Science

Enterprise Document Intelligence [Vol.1 #4bis] - A coauthor note on the brick-by-brick pitfalls that justified the four-brick split, before Part II walks the fi

CPUs, GPUs, TPUs, and NPUs The post The Hardware That Makes AI Possible appeared first on Towards Data Science .

Stop re-computing the same context. Learn how to build a C++ runtime with copy-on-fork KV snapshots to eliminate redundant LLM prefills in multi-agent pipelines

Follow this framework to build a project that will impress hiring managers The post The Exact ML Project I’d Build to Get Hired in 2026 appeared first on Toward

Building an ML football forecaster in R The post Can Machine Learning Predict the World Cup? appeared first on Towards Data Science .

This is how LLMs are used today to increase precision in recommendation systems The post Increase Recommendation Systems’ Precision with LLMs, Using Python appe

Quantum Machine Learning promises powerful new ways of processing information, but quantum states are extraordinarily fragile. In this article, we explore why q

Get the most out of Claude Code with these four techniques The post 4 New Techniques to Maximize Claude Code appeared first on Towards Data Science .

What Fourier analysis misses The post Sequential Fitting: A Different Perspective on the Spectral Bias of Neural Networks appeared first on Towards Data Science

The clipping bug has lived in every 3D simulation pipeline for three decades. Here is exactly why it happens, how the math breaks, and how swapping one equation

Because the alternative is much too dangerous The post We Should Train AI to Betray Its Users appeared first on Towards Data Science .

An introduction to multi-agent systems The post Building a Multi-Agent System in Python appeared first on Towards Data Science .

My approach to guiding the choice between Eppo and Statsig, and the lessons learned The post Picking an Experimentation Platform: A Retrospective appeared first

Building a forecast from Elo, Poisson, and 10,000 simulations The post Who Will Win the 2026 Soccer World Cup? appeared first on Towards Data Science .

what it costs, what it gains and the three mistakes that I make The post My SciPy ODE Solver Was Killing My Bayesian Inference: A Cosmologist’s Honest Account o

I got tired of copying files into an AI chat just to get feedback. So I built a pure Python MCP server that gives AI tools direct access to my local project—no

How a simple choice shapes exploration, safety, and efficiency The post The Fundamental Choice in Reinforcement Learning: On‑Policy vs. Off‑Policy appeared firs

Using DSPy to automatically create, evaluate, and optimize your prompts The post Automate Writing Your LLM Prompts appeared first on Towards Data Science .

Python tutorial for fine-tuning a Mistral Small 3.1 on an imbalanced training set to classify 15 emotions in social media communication The post How to Fine-Tun

Abacus.AI and the case for unified AI workflows The post How to Navigate the Shift from Prompt-Based Tools to Workflow-Driven AI appeared first on Towards Data

In Part 1 of this series, we introduced Chronos-2, a time-series foundation model. We got our hands dirty by walking through a real case study and saw what Chro

When images, mosaics, and data cubes exist in abundance, but field labels are expensive, rare, and imperfect. The post Small Data, Big Maps: Training Geospatial

Understanding how FPN allows deep learning models detecting small objects and how to implement it from scratch The post FPN Paper Walkthrough: Leveraging the In

A look at the real-world value of online graduate AI programs, combining hard data with firsthand experience of a big tech machine learning engineer The post Is