It is a necessity that anyone should follow some podcasts and blogs for his/her field. ML is not an exception. This is the stuff I find useful, and I try to read or watch them every now and then.
ML People (Blogs)
- Andrej Karpathy Andrej Karpathy - Andrej Karpathy blog
- Yann LeCun Yann LeCun’s Home Page
- Andrew Ng https://www.andrewng.org
- Chris Olah Home - colah’s blog
- Alfredo Canziani atcold.github.io
- Cassie Kozyrkov
- Demis Hassabis
- Geoffrey Hinton
- Yoshua Bengio
- Kate Crawford - Atlas of AI
- Lex Fridman
- Soumith Chintala
- Yoshua Bengio -
- ruder.io ++
- Rachel Thomas, PhD - an AI researcher going back to school for immunology
- Julia Evans
- Stephen Merity
- Cate Huston
- Slav Ivanov
- Julia Ferraioli
- Lil’Log
- Matt Might’s blog
- State of the Smerity
- François Chollet | Substack
- Denny’s Blog
- Strange Loop Canon | Rohit Krishnan | Substack
ML Sites
- Distill — Latest articles about machine learning
- The latest in Machine Learning | Papers With Code
- fast.ai - fast.ai—Making neural nets uncool again
- Home - Papers
- The AiEdge Newsletter | Substack
Comprehensive ML Tutorials
- Harvard CS197: AI Research Experiences
- ML Story
- Deep Learning Book
- PyTorch Deep Learning - atcold: Deep Learning course by Yan Lecun
- Dive into Deep Learning
- UvA Deep Learning Tutorials
- Data Science at the Command Line
- Mathematics for Machine Learning
- CS231n Convolutional Neural Networks for Visual Recognition
- Unsupervised Feature Learning and Deep Learning Tutorial
- Neural networks and deep learning
- GitHub - jlevy/the-art-of-command-line: Master the command line, in one page
- BE/Bi 103 a: Introduction to Data Analysis in the Biological Sciences — BE/Bi 103 a documentation
- Machine Learning Crash Course by Google
MLOps and ML System Design
- Made With ML
- CS 329S: Machine Learning Systems Design
- GitHub - EthicalML/awesome-production-machine-learning: A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
- GitHub - featurestoreorg/serverless-ml-course: Serverless Machine Learning Course for building AI-enabled Prediction Services from models and features
Python Great Tutorials
Probability
- Probability, Statistics & Random Processes | Free Textbook | Course
- Five Minute Stats
- Welcome to STAT 415! | STAT 415
- https://web.stanford.edu/~lmackey/stats300a/
- https://vioshyvo.github.io/Bayesian_inference/index.html
- https://stephens999.github.io/fiveMinuteStats/MH_intro.html
Good Books
- No Bullshit Guide to Math
- No Bullshit Guide to Linear Algebra
Great ML Books
In my opinion, these books are the best books to get a professional in ML field.
- The 100 Page Machine Learning Book
- CS229 Lecture Notes
- Learning From data: A short course
- Deep Learning, MIT 2017
- Pattern Recognition and Machine Learning
- The elements of statistical Learning
Great ML Podcasts
ML Newsletters
Reddit Communities
Useful Libraries
Other people’s lists
- aman.ai • exploring the art of artificial intelligence
- My Curated List of AI and Machine Learning Resources from Around the Web
- Machine Learning Guide - Resources
- How to Become a Data Scientist at Your Own | Kaggle
Others
- https://docs.ray.io/en/latest/tune/index.html
- https://labs.play-with-docker.com/
- https://www.v7labs.com/blog/yolo-object-detection
- https://github.com/wangdongdut/PaperWriting
- https://holoviz.org/index.html
- https://koaning.github.io/human-learn/index.html
- https://blog.ncase.me/
- http://worrydream.com/
- https://www.jefkine.com/
- http://csrankings.org/advice.html
- Michael Nielsen
- Blog - WriteIvy - How to write SOP