Resources

Here is a list of data science resources, personal blogs and technical writings that I was finding myself more or less going back to from time to time. Eventually I’ve decided that a list of them was needed.

• Personal websites & blogs
  • Eugene Yan
  • Chan`s Jupyter
  • Vicki Boykis
  • Chip Huyen’s Blog
  • Sebastian Raschka, PhD
  • a how-to blog • Susan Shu Chang
  • swyx’s site • Shawn Wang
• Papers
  • ApplyingML
  • Papers with Code
  • Large Language Model (LLM) Reading List • GitHub
  • Anti-hype LLM reading list • veekaybee/normcore-llm.md • GitHub Gist
  • The Practical Guides for Large Language Models • GitHub
• Notes
  • Chris Albon’s Study Notes
  • Oh Shit, Git!?!
• Interview preparation
  • Introduction to Machine Learning Interviews Book • MLIB
  • Data Science Interview Questions & Answers • GitHub
  • Data Science Interview Questions • GitHub
  • A Life After Layoff • YouTube
• Presentation skills
  • Storytelling with data
• Learning resources
  • The Full Stack Website
  • Practical Deep Learning for Coders • fast.ai
  • Deep Learning Fundamentals • Lightning AI
  • Alexey Grigorev’s ML Zoomcamp • GitHub
  • Alexey Grigorev’s MLOps Zoomcamp • GitHub
  • Alexey Grigorev’s LLM Zoomcamp • GitHub
  • Neural Networks and Deep Learning • Michael Nielsen
  • MIT Open Learning Library
  • The Alan Turing Online Learning Platform
  • CS231n: Deep Learning for Computer Vision • Stanford Online
  • CS224N: Natural Language Processing with Deep Learning • Stanford Online
  • CS25: Transformers United V4 • Spring 2024 • Stanford Online
  • Probabl YouTube channel • YouTube
  • Machine Learning for Beginners • A Curriculum
• Podcasts
  • Machine Learning Street Talk • YouTube
  • DataTalksClub • YouTube
  • The Real Python Podcast • YouTube
  • Astronomers Turned Data Scientists Podcast • Podbean
  • The Turing Podcast • The Alan Turing Institute
• Others
  • Trending repositories on GitHub today • GitHub
  • Compact Awesome CV • GitHub