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9 Best Data Science RSS Feeds in 2026

9 feeds from 9 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.

  1. 1Towards Data Sciencetowardsdatascience.com · about 24 posts a weekPublish AI, ML & data-science insights to a global community of data professionals.Last post 8 Nov
    Website
  2. 2R-bloggersr-bloggers.com · about 15 posts a weekR news and tutorials contributed by hundreds of R bloggersLast post 7 Nov
    Website
  3. 3Statistical Modeling, Causal Inference, and Social Sciencestatmodeling.stat.columbia.edu · about 12 posts a weekLast post 8 Nov
    Website
  4. 4KDnuggetskdnuggets.com · about 11 posts a weekData Science, Machine Learning, AI & AnalyticsLast post 6 Nov
    Website
  5. 5FlowingDataflowingdata.com · about 10 posts a weekStrength in NumbersLast post 9 Nov
    Website
  6. 6Analytics Vidhyaanalyticsvidhya.com · about 5 posts a weekLearn everything about AnalyticsLast post 5 Nov
    Website
  7. 7Machine Learning Masterymachinelearningmastery.com · about 5 posts a weekMaking developers awesome at machine learningLast post 7 Nov
    Website
  8. 8The Puddingpudding.cool · about 3 posts a monthThe Pudding is an editorial publication that explains ideas debated in culture with visual essays.Last post 3 Nov
    Website
  9. 9Eugene Yaneugeneyan.comEugene 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
    Website

Latest data science posts

  1. A brain from simple circuits

    · flowingdata.com · Nathan Yau

    Aatish Bhatia and Arkarup Banerjee use a visual explainer for how a few… Tags: Aatish Bhatia , Arkarup Banerjee , brain , Myriad , neurons

  2. How to Build Multi-Agent Systems with the OpenAI Agents SDK

    · towardsdatascience.com · Shuai Guo

    Build an EV purchase adviser and a support agent in Python, then see how fan-out, pipelines, hierarchies, and swarms reuse the same building blocks. The post How to Build Multi-Agent Systems with the OpenAI Agents SDK appeared first on Towards Data Science .

  3. “Causal Effects Versus Causal Mechanisms: Two Traditions With Different Requirements and Contributions Towards Causal Understanding”

    · statmodeling.stat.columbia.edu · Andrew

    Following up on our post from last year on the importance of mechanistic models, Jim Grace points to his above-titled paper in Ecology Letters. From the abstract: When methods are described as ‘causal,’ emphasis is increasingly placed on statistical techniques … Continue reading →

  4. Change One Monty Hall Rule and Five LLMs Still Say Switch

    · towardsdatascience.com · Utkarsh Mangal

    Even with step-by-step reasoning, the models landed near 33% accuracy, and one quoted the host's rule correctly before ignoring it. The post Change One Monty Hall Rule and Five LLMs Still Say Switch appeared first on Towards Data Science .

  5. 2026 compared to other dramatic midterm election reversals of the past half-century

    · statmodeling.stat.columbia.edu · Andrew

    As I said a few days ago, you don’t me anymore to do your fancy post-election data analyses. So instead I can offer speculation (Could the 2026 election results lead to a decrease in political polarization?) and meta-commentary (NYT columnist … Continue reading →

  6. Floating-Point Precision and Its Effects to Model Inference

    · machinelearningmastery.com · Adrian Tam

    Overview This post is divided into five parts; they are: • How Floating-Point Numbers Work • Common Precision Formats • Loading a Model at a Different Precision • Mixed Precision and Sensitive Operations • Measuring the Result How Floating-Point Numbers Work A floating-point number contains a sign…

  7. Using caretS3 with ahead::ctxthetaf for Time Series Forecasting

    · r-bloggers.com · T. Moudiki

    A demonstration of using caretS3 models for time series forecasting with ahead::ctxthetaf. Continue reading : Using caretS3 with ahead::ctxthetaf for Time Series Forecasting

  8. Free AI and Data Courses with 365 Data Science: 100% Unlimited Access until Nov 20

    · kdnuggets.com · KDnuggets

    Get unlimited free access to 365 Data Science’s complete AI and data learning platform, including 134 courses, hands-on projects, and certifications, through November 20.

  9. How to Give Your AI Agent Memory

    · kdnuggets.com · Abid Ali Awan

    Learn how to give AI agents long-term memory using the OpenAI Agents SDK, Mem0, and MCP to remember preferences, context, and important information across sessions.

  10. Free AI and Data Courses with 365 Data Science: Unlimited Access until Nov. 20

    · r-bloggers.com · neddd

    365 Data Science opens its doors this November 100% for free! From November 5 to November 20, 2026, enjoy unlimited access to the entire platform, including a wide range of R programming courses and projects. This offer…

  11. DiffusionGemma: Hands-On with Google’s Text Model That Writes All at Once

    · machinelearningmastery.com · Shittu Olumide

    In this article, you will learn what DiffusionGemma is, how its diffusion-based text generation differs from standard autoregressive language models, and how to run it...

  12. Swings in Texas over the years

    · flowingdata.com · Nathan Yau

    The New York Times produced a series of charts for the shift in… Tags: elections , New York Times , partisanship , Texas

  13. GPT Image 2.6: The Best Image Generation Model Just Got an Upgrade!

    · analyticsvidhya.com · Vasu Deo Sankrityayan

    What if you could turn a rough sketch into a polished design, edit an image with a few annotations, or create an animated GIF from a single prompt? OpenAI’s new Images 2.6 promises exactly that, bringing new creative possibilities to ChatGPT, Codex, and the API. But how well does it handle the…

  14. 7 Best AI Agent Collaboration Platforms in 2026

    · analyticsvidhya.com · Vasu Deo Sankrityayan

    Building an AI agent is one thing. Making it available to an entire team is another. Shared access, permissions, integrations, and reusable workflows determine whether an agent becomes a reliable team resource or another setup everyone must recreate. Platforms approach this differently. Some share…

  15. The Afterlife of Pi

    · pudding.cool

    A 150-year visual history of what happened to the digits of pi after they were calculated.

  16. lo-pi radio

    · pudding.cool

    Live lo-fi beats from the digits of pi, forever.

  17. Python in Marketing: A Practical Guide to Marketing Analytics, Automation, and Data-Driven Growth [Full Book]

    · freecodecamp.org · Eva J Patel

    Marketing has always involved wrangling lots of data. Before digital marketing, businesses had to track sales, customer purchases, coupon redemptions, store traffic, and survey responses to understand

  18. How to Build a Simple Data Analyzer in Python with Pandas

    · freecodecamp.org · Eva J Patel

    Data analysis might sound complicated when you first encounter it. You might imagine large databases, advanced mathematics, and complicated machine learning algorithms. But many useful data analysis t

  19. Why Data Modeling Is Not Enough

    · sloanreview.mit.edu · Jeffrey D. Camm, Michael J. Fry, and Scott M. Shafer. Jeffrey D. Camm is senior associate dean of faculty and research, a professor of analytics, and the Inmar Presidential Chair in Analytics at the Wake Forest University School of Business. Michael J. Fry is a professor of operations, business analytics, and information systems and senior director of the centers and institutes in the Lindner College of Business at the University of Cincinnati. Scott M. Shafer is senior associate dean of academic programs and a professor of operations management at the Wake Forest University School of Business.

    Otto Dettmer/Ikon Images Imagine that, as an operations manager at a global retailer, you have invested heavily in data science. Your data science team has built sophisticated models that produce demand predictions for the company’s products with impressive accuracy. Yet, when the CEO, seeking to…

  20. How to Make Zero-Training Tabular Predictions with NVIDIA Structured Data Models

    · marktechpost.com · Sana Hassan

    In this tutorial, we implement Structured Data Models, NVIDIA’s new library that puts several pretrained foundation models for tables behind one PyTorch interface, and use it to make predictions without training. The library wraps TabICLv2 and KumoTabular for single tables and KumoRelational for…