Full commentary and notes here ➡️: https://www.trybackprop.com/blog/top_ml_learning_resources

Used these to brush up on math and teach myself AI/ML over the course of two years. I'm now a staff ML engineer at FAANG. Hope these help.

Fundamentals

• Linear Algebra – 3Blue1Brown's Essence of Linear Algebra series, binged all these videos on a one hour train ride visiting my parents
• Multivariable Calculus – Khan Academy's Multivariable Calculus lessons were a great refresher of what I had learned in college. Looking back, I just needed to have reviewed Unit 1 – intro and Unit 2 – derivatives.
• Calculus for ML – this amazing animated video explains calculus and backpropagation
• Information Theory – easy-to-understand book on information theory called Information Theory: A Tutorial Introduction.
• Statistics and Probability – the StatQuest YouTube channel

Machine Learning

• Stanford Intro to Machine Learning by Andrew Ng – Stanford's CS229, the intro to machine learning course, published their lectures on YouTube for free. I watched lectures 1, 2, 3, 4, 8, 9, 11, 12, and 13, and I skipped the rest since I was eager to move onto deep learning. The course also offers a free set of course notes, which are very well written.
• Caltech Machine Learning – Caltech's machine learning lectures on YouTube, less mathematical and more intuition based

Deep Learning

• Andrej Karpathy's Zero to Hero Series – Andrej Karpathy, an AI researcher who graduated with a Stanford PhD and led Tesla AI for several years, released an amazing series of hands on lectures on YouTube. highly highly recommend
• Neural networks – Stanford's CS231n course notes and lecture videos were my gateway drug, so to speak, into the world of deep learning.

Transformers and LLMs

• Transformers – watched these two lectures: lecture from the University of Waterloo and lecture from the University of Michigan. I have also heard good things about Jay Alammar's The Illustrated Transformer guide
• ChatGPT Explainer – Wolfram's YouTube explainer video on ChatGPT
• Interactive LLM Visualization – This LLM visualization that you can play with in your browser is hands down the best interactive experience with an LLM.
• Financial Times' Transformer Explainer – The Financial Times released a lovely interactive article that explains the transformer very well.
• Residual Learning – 2023 Future Science Prize Laureates Lecture on residual learning.

Efficient ML and GPUs

• How are Microchips Made? – This YouTube video by Branch Education is one of the best free educational videos on the internet, regardless of subject, but also, it's the best video on understanding microchips.
• CUDA – My L8 and L9 FAANG coworkers acquired their CUDA knowledge from this series of lectures.
• TinyML and Efficient Deep Learning Computing – 2023 lectures on efficient ML techniques online.
• Chip War – Chip War is a bestselling book published in 2022 about microchip technology whose beginning chapters on the invention of the microchip actually explain CPUs very well