Study Notes
A knowledge rebuilding ladder from probability to transformers from my Stanford notes.
- 01Probability Foundations
- 02Linear Algebra
- 03Statistical Inference
- 04Linear Models
- 05Stochastic Processes
- 06aStatistical Learning I
- 06bStatistical Learning II
- 07Bayesian Statistics
- 08Time Series
- 09Causal Inference
- 10Convex Optimization
- 11aDeep Learning: Training Dynamics & Vision
- 11bSequence Models, Attention & Transformers
- 12Reinforcement Learning
- 13aAlgorithms I: Analysis, Divide & Conquer, and Data Structures
- 13bAlgorithms II: Graphs, Dynamic Programming, Greedy & Flows