Lecture 1. Introduction to Python with Linear Algebra [slides]
Supplementary: Anaconda Distribution; Quiz 1
Lecture 2. Gradient Descent and Perceptron
Lecture 3. Linear Regression
Lecture 4. Bayes' Rule
Lecture 5. Bayesian Learning
Lecture 6. Exact Bayesian Inference
Lecture 7. A Maximum Likelihood Approach
Lecture 8. Bias-Variance Trade-Off and Bayesian Regression
Lecture 9. Bayesian Linear Classifier with JAX
Lecture 10. Markov Chain Monte Carlo Method
Lecture 11. Bayesian Nonlinear Classifier
Lecture 12. Non-Probabilistic Classifiers
Lecture 13. Deep Learning and Neural Networks
