- Watching list
- Course lectures
- YouTube channels to follow
- Jay’s Visual Intro to AI by Jay Alammar, STV Capital
- AI for Full-Self Driving by Andrej Karpathy, Tesla
- Backprop in ConvNets by Prof. Dhruv Batra, Virginia Tech
- PyTorch at Tesla by Andrej Karpathy, Tesla
- Heroes of Deep Learning: Andrew Ng interviews Andrej Karpathy, Tesla
- Talk: machine learning and causal inference by Susan Athey, Stanford
- A curated list of YouTube channels and videos that I follow/recommend to build intuition around AI/ML concepts.
- Official YouTube channels of Stanford University/School of Engineering.
- Recommended playlists: CS229: Machine Learning, CS230: Deep Learning and CS231n: Convolutional Neural Networks for Visual Recognition
- Official YouTube channel of MIT OCW.
- Course lectures for MIT 6.S191: Introduction to Deep Learning.
- Course lectures for MIT 6.S094: Deep Learning and other related lectures.
- Lex is also the host behind the Artificial Intelligence podcast.
- Course lectures for NYU’s Deep Learning (with PyTorch).
YouTube channels to follow
- 3Blue1Brown, by Grant Sanderson, explains concepts using a combination of math and entertainment.
- The goal is for explanations to be driven by animations and for difficult problems to be made simple with changes in perspective.
- New videos every Sunday.
Two Minute Papers
- Awesome explanations of the latest and greatest research papers.
- Two new videos every week.
StatQuest with Josh Starmer
- Basics stats/ML concepts clearly explained.
- Recommended: Support Vector Machines, Clearly Explained
- Videos about AI/ML research papers, programming, and issues of the AI community and the broader impact of AI in society.
- Creator of the famous GPT-3, GPT-2 and Attention Is All You Need explanation videos.