How moving randomness outside the computation graph turns noisy gradient estimators into low-variance, differentiable ones

The post Reparameterization Tricks: Variance Reduction by Smarter Gradients appeared first on Towards Data Science.

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 Science.

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 first on Towards Data Science.

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 — and exactly how much more data buys you.

The post How Many Labeled Examples Does a Text Classifier Actually Need? I Measured It. appeared first on Towards Data Science.

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 Model’s MSE Is Lying to You appeared first on Towards Data Science.

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 Use One Model and When to Use a Team of Agents appeared first on Towards Data Science.

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 prompt, context, and loop engineering, and why it matters.

The post Graph Engineering for AI Agents: From Prompts and Loops to Workflows appeared first on Towards Data Science.

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 Dynamic Skills: A Different Model for Agent Knowledge appeared first on Towards Data Science.

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 Can Call It appeared first on Towards Data Science.

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 appeared first on Towards Data Science.

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 Breaking My AI Support Bot, and It Wasn't in the New Model appeared first on Towards Data Science.

What large operators can teach us about turning alert fatigue into faster, safer service assurance

The post Stop Managing Alarms: An Incident-First Blueprint for Telecom AIOps appeared first on Towards Data Science.

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

The post Coding Agents Don't Need Longer History — They Need Intent Continuity appeared first on Towards Data Science.

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% Illusion: Why Your Confidence Interval Isn't What You Think It Is appeared first on Towards Data Science.

Clarifying the math behind Anthropic’s representation workspace

The post Demystifying Anthropic's J-Space: A Mathematical Primer appeared first on Towards Data Science.

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 Data Science.

Moving from static model assignment to intelligent, task-level LLM selection.

The post Optimizing LLM Inference Costs in Multi-Agent Systems with Adaptive Model Routing appeared first on Towards Data Science.

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 Data Science.