📰 Towards Data Science

Robust Estimation Series: comparing classical and modern robust estimators through theory, code, and experiments The post How to Make Linear Regression Survive

PyTorch and TensorFlow tensor broadcasting: how silent shape errors cause difficult-to-debug machine learning bugs The post Silent Broadcasting Can Ruin Your Mo

A VRAM budget formula for LLM serving, and three optimization strategies mapped to the traffic patterns that trigger the OOM. The post The KV Cache Tax: Why Inf

What ordering and not eating a large pizza tells us about ML memory management The post The N Squared Pizza Problem appeared first on Towards Data Science .

How moving randomness outside the computation graph turns noisy gradient estimators into low-variance, differentiable ones The post Reparameterization Tricks: V

Keep your apps looking professional with Claude Code design skills The post How to Build Consistent Designs with Claude Code appeared first on Towards Data Scie

How statistical moments connect the mean, the variance, and higher powers of a distribution The post Seizing the Moment: The Hidden Silhouette of Data appeared

Before reaching for an LLM API on every classification problem, it's worth knowing what a decades-old baseline can already do with the labeled data you have — a

First in a series on probabilistic forecasting for physical signals. Next: what happens when you roll the forecast forward more than one step. The post Your Mod

When Codex is the right shape for the problem, when Claude Code is, and how I split 5 specialist agents between them on dense AI capacity work. The post When to

A viral debate over loops versus graphs points to a bigger shift in how we build AI systems. Here’s what graph engineering actually means, how it differs from p

Why the skill-inflation panic is aimed at the wrong thing, and what it costs to make agent knowledge a build artifact instead of a file. The post From Static to

Building a FastAPI endpoint for churn prediction, and everything that broke between "it runs" and "it's live The post Your Model Isn't Done Until Someone Else C

A practitioner's guide to estimating what an opt-in AI feature actually did, when nobody randomized it. The post Your AI Adoption Lift Is a Selection Effect app

A real Weave project that regression-tests three OpenAI models against the exact reply format your app depends on. The post One Capital Letter Was Silently Brea

What large operators can teach us about turning alert fatigue into faster, safer service assurance The post Stop Managing Alarms: An Incident-First Blueprint fo

I built a system that automatically discovers, verifies, and applies relevant requirements from earlier interactions without asking the user where they came fro

Why AI coding makes software design more important The post Software Design in the Age of AI appeared first on Towards Data Science .

Frequentist confidence intervals and Bayesian credible intervals answer different questions, and confusing them can distort product decisions The post The 95% I

Clarifying the math behind Anthropic’s representation workspace The post Demystifying Anthropic's J-Space: A Mathematical Primer appeared first on Towards Data

Better understand the intent of your coding agents The post How to 5x Your Communication Effectiveness with Claude Code appeared first on Towards Data Science .

Why autonomous agents expose a new explainability problem in fraud detection The post What SHAP Can't Explain About Agentic AI Fraud appeared first on Towards D

Moving from static model assignment to intelligent, task-level LLM selection. The post Optimizing LLM Inference Costs in Multi-Agent Systems with Adaptive Model

A model is only as reliable as the assumptions behind it The post Who Questions What Works: When Should We Retest Our Assumptions? appeared first on Towards Dat