Statistical thinking beyond formulas

The post 10 Statistical Traps We Often Overlook appeared first on Towards Data Science.

AI companies quietly watermark billions of words a day. Here’s how to apply the same three families of techniques to your own writing—and what real experiments reveal about which watermarks survive copy-paste, editing, and paraphrasing.

The post Text Watermarking in Python: Catch Whoever Copies Your Writing appeared first on Towards Data Science.

Using LDA for dimensionality reduction in classification problems

The post Linear Discriminant Analysis (LDA) in Real-Life: Dimensionality Reduction in a Real-Estate Dataset appeared first on Towards Data Science.

Why the default 50/50 split is the wrong move when your treatment is more expensive than your control, and how cost-based sampling weights fix it

The post Optimal Traffic Allocation Under Heterogeneous Variant Cost appeared first on Towards Data Science.

Power BI Premium is gone. Microsoft Fabric took its place. Here's what actually changed for you, what didn't, and where to start — without the panic.

The post The Power BI Developer's Survival Guide to Microsoft Fabric appeared first on Towards Data Science.

Why the standard groupBy function isn’t enough

The post A Practical Introduction to PySpark Window Functions appeared first on Towards Data Science.

What each one solves, and runnable code you can paste into a notebook.

The post 5 AI Skills That Will Keep Data Scientists Relevant in 2027 appeared first on Towards Data Science.

Quick and simple tips to help you write better agent instructions

The post 8 Tips for Writing Effective Agent Instructions appeared first on Towards Data Science.

How to apply the latest context engineering guidelines to your day-to-day data science work

The post Context Engineering Is Changing. Here’s What It Means for Data Scientists appeared first on Towards Data Science.

As AI handles more of the execution, what work should belong to agents vs humans and why does that distinction matter?

The post Agentic AI Is Rewriting The Analytics Stack But There's One Skill It Still Can't Touch appeared first on Towards Data Science.

Bagging hits a wall no amount of trees can break — here's the equation that explains why, and the experiment that proves it

The post Why Random Forest Needs to Be This Random appeared first on Towards Data Science.

We're excited to share some big news: We completely rebuilt the TDS website and our contributor portal. Whether you come here to read, to write, or both, here's what you can expect from our new site.

The post A New Towards Data Science: A Faster Site and a Brand-New Contributor Portal appeared first on Towards Data Science.

What moving a Dockerized pipeline off my laptop taught me about containers, networking, and hidden assumptions.

The post I Deployed My Data Pipeline to AWS. Then Everything That Was “Local” Broke. appeared first on Towards Data Science.

A practical guide to navigate hierarchies, find routes, detect cycles and calculate degrees of separation

The post Recursive CTEs: SQL’s Hidden Graph Traversal Engine appeared first on Towards Data Science.

From Kaplan-Meier curves to hazard ratios with runnable Python Code throughout

The post Survival Analysis and the Cox Proportional Hazards Model: A Beginner-Friendly Guide appeared first on Towards Data Science.

Dimensions are one of the two main object types in dimensional modelling. But what are the different types of dimensions? And how can you use them?

The post The Types of Dimensions in a Star Schema, and How to Use Them appeared first on Towards Data Science.

From Kaplan-Meier curves to hazard ratios with runnable Python Code throughout

The post Survival Analysis and the Cox Proportional Hazards Model: A Beginner-Friendly Guide appeared first on Towards Data Science.

Dimensions are one of the two main object types in dimensional modelling. But what are the different types of dimensions? And how can you use them?

The post The Types of Dimensions in a Star Schema, and How to Use Them appeared first on Towards Data Science.

A production account of scaling an enterprise integration pipeline from 500 to 8,000 events per second, and the two correctness guarantees the throughput work was never allowed to trade away.

The post How to Scale an Integration Pipeline Without Breaking Correctness appeared first on Towards Data Science.

For years, web agents have worked one click at a time—and often fallen apart on long tasks. Microsoft Research’s Webwright makes a different bet: give the model a terminal and let it write the program instead. On long-horizon tasks, the same GPT-5.4 model jumps from 33.5% to 60.1% success. And instead of leaving behind a click trace, it leaves something you can actually use again: a command-line tool.

The post Webwright: Why AI Web Agents Should Write Code, Not Click appeared first on Towards Data Science.