Lecture 1. Introduction to Python with Probability [slides]
Supplementary: Anaconda Distribution; Quiz 1
Lecture 2. Relative Frequency and Python Simulations [slides]
Supplementary: Four-Door Problem; Quiz 2
Lecture 3. Bayes' Rule [slides]
Supplementary: Quiz 3b
Lecture 4. Bayesian Learning [slides]
Supplementary: Quiz 4
Lecture 5. Exact Bayesian Inference [slides]
Supplementary: Posterior; Exam 1
Lecture 6. A Least Squares Approach [slides]
Supplementary: Olympic data; Regression with sklearn; Kaggle housing preprocessing; Exam 2a
Lecture 7. A Maximum Likelihood Approach
Lecture 8. Bias-Variance Trade-Off
Lecture 9. Bayesian Classifiers
Lecture 10. Probabilistic Classifiers
Lecture 11. Unsupervised Machine Learning
Lecture 12. Introduction to Deep Learning
