Topics /
8 Best Data Science RSS Feeds in 2026
8 feeds from 8 sites tagged “data science”, ranked by how many people follow each one in their readers, how often it posts and how recently. The list moves as the feeds are checked, every few hours at least.
- 1Towards Data SciencePublish AI, ML & data-science insights to a global community of data professionals.Last post 24 Sept
- 2Statistical Modeling, Causal Inference, and Social ScienceLast post 24 Sept
- 3KDnuggetsData Science, Machine Learning, AI & AnalyticsLast post 24 Sept
- 4R-bloggersR news and tutorials contributed by hundreds of R bloggersLast post 23 Sept
- 5FlowingDataStrength in NumbersLast post 24 Sept
- 6Machine Learning MasteryMaking developers awesome at machine learningLast post 24 Sept
- 7The PuddingThe Pudding is an editorial publication that explains ideas debated in culture with visual essays.Last post 4 Aug
- 8Eugene YanEugene Yan works at the intersection of consumer data & tech to build machine learning products, and writes about effective data science, learning & career.Last post 21 Jun
Latest data science posts
How to Maximize Your Coding Agent Subscriptions
Get more out of your coding agent subscriptions The post How to Maximize Your Coding Agent Subscriptions appeared first on Towards Data Science .
MCP Explained in 5 Minutes
A visual guide to MCP that explains how it works, how to use it with Claude Code, Tavily, GitHub, and Playwright, and what is new through simple diagrams that make the whole concept easy for anyone to understand.
Beyond RAGs: Building Actually Truthful AI Harnesses
Retrieval is not evidence. How to build AI that proves its own claims. The post Beyond RAGs: Building Actually Truthful AI Harnesses appeared first on Towards Data Science .
It’s fine to use computer-generated survey responses—if you don’t care about the data anyway!
Think about it like this: a survey organization uses a method M to get data D to give population estimates E which are used by clients to make actions A. The method M is crucial in determining data D, which … Continue reading →
Towards Spec-Driven Test Automation: Part 1
Why a green test suite can mean nothing The post Towards Spec-Driven Test Automation: Part 1 appeared first on Towards Data Science .
What I’ve Learned About DeepSeek Harness
KDnuggets team member Shittu Olumide tested out DeepSeek Harness. Here's what he found.
Agent or Workflow? A Practical Test for Knowing When You Actually Need an AI Agent
In this article, you will learn the key differences between AI workflows and agents, and how to decide which approach is right for your use...
Illustration of 30 WNBA seasons
Celebrating 30 seasons of the WNBA, ESPN has a fun piece on the… Tags: basketball , ESPN , WNBA
✚ Visualization tools, datasets, and learning resources — September 2026 roundup
Here's what happened in September. Tags: roundup
When the Correct Answer Is Nothing, What Does Your Pipeline Return?
The reliability mechanisms we add to LLM pipelines are often the ones that make them confidently wrong. The post When the Correct Answer Is Nothing, What Does Your Pipeline Return? appeared first on Towards Data Science .
I Trained a Tiny Network to Compress Data. It Drew a Pentagon.
Reproducing Anthropic's "Toy Models of Superposition" from scratch in NumPy, with hand-derived gradients and no borrowed numbers. The post I Trained a Tiny Network to Compress Data. It Drew a Pentagon. appeared first on Towards Data Science .
Everything Claude Opus 5.5 Actually Ships With
This article pulls together every verifiable number and detail from Anthropic's announcement, the platform documentation, the system card, and independent coverage, so you have one place to check the facts.
Why Most Data Science Notebooks Die After Day One: How to Build Ones That Survive
Six habits that keep a notebook runnable after you close the laptop.
From Words to Vectors: What Happens in Between?
A Journey through TF-IDF, vector space, and text classification The post From Words to Vectors: What Happens in Between? appeared first on Towards Data Science .
Here’s a causal inference problem: where did the estimate of $64 million come from in “Blake Lively Says She Suffered $64 Million Financial Fallout From Justin Baldoni Conflict . . .”?
OK, here’s a causal inference problem for ya: Blake Lively Says She Suffered $64 Million Financial Fallout From Justin Baldoni Conflict . . . In Lively’s memorandum in opposition to Wayfarer Studios’ motion in limine filed April 17, her expert … Continue reading →
How GRPO Trains Small Language Models with Verifiable Rewards
The mechanics behind local reasoning experiments with Unsloth and why the reward function matters as much as the model. The post How GRPO Trains Small Language Models with Verifiable Rewards appeared first on Towards Data Science .
RAG vs. Fine-Tuning for Domain Adaptation: When to Use Which
In this article, you will learn the mechanical difference between retrieval-augmented generation and fine-tuning, when each technique is the right tool, and how to decide...
High-Performance Data Processing with Polars: A KDnuggets Cheat Sheet
Polars is a DataFrame library written in Rust on the Apache Arrow memory format, and the speed comes less from the language than from the model. The model? Describe your work as expressions, and the Polars query engine plans them out.
How to Make Your First World Model from Scratch
A beginner-friendly guide to building a world model in Python, letting it daydream its way through CartPole, and accurately measuring when the illusion collapses. The post How to Make Your First World Model from Scratch appeared first on Towards Data Science .
Biggest political donors so far
Using data from the Federal Election Commission, the Washington Post called out the… Tags: donors , election , politics , Washington Post
