Lecture 1. History of Artificial Neural Network [slides]
Supplementary: Anaconda Distribution; Prediction Machines; Quiz 1b
Lecture 2. The Rosenblatt Perceptron [slides]
Supplementary: Quiz 2b
Lecture 3. Introduction to Linear Algebra with Python [slides]
Supplementary: Math behind LLMs; Quiz 3b
Lecture 4. Linear Regression
Lecture 5. Bayes' Rule
Lecture 6. Bayesian Learning
Lecture 7. Exact Bayesian Inference
Lecture 8. A Maximum Likelihood Approach
Lecture 9. Bias-Variance Trade-Off and Bayesian Regression
Lecture 10. Bayesian Linear Classifier with JAX
Lecture 11. Markov Chain Monte Carlo Method
Lecture 12. Bayesian Nonlinear Classifier
Lecture 13. Non-Probabilistic Classifiers
Lecture 14. Deep Learning and Neural Networks
