Detailed step-by-step process for learning ML
Probability: Harvard Stat 110 by Blitzstein - Youtube videos and book
Statisitics: MIT lectures by Philip Riggolet MIT 18.650
Linear Algebra: Lectures by Gilbert Strang(original) MIT 18.06 Lectures by Gilbert Strang( Matrix methods in Signal Processing) MIT 18.065
Machine learning : CS4780 by Kilian Weinberger 2019
CS229 Original Stanford Vidoes from Andrew Ng 2008 version ( not the watered down coursera version)
Deep Learning: Deep learning web book by Michael Nielsen
CS224 Stanford - for NLP CS231 Stanford - for Vision Try to take the latest offering available on youtube
Advanced: PGM by Eric Xiang CMU 10-708
Reinforcement Learning : 10 lectures by David Silver
Nice concepts:
