Course materials by Dr. Aijun Zhang, Fall 2020
Lecture 1: Introduction (Slides; Python)
Lecture 2: Data Exploration (Slides; Python)
Lecture 3: Generalized Linear Models (Slides; Python)
Lecture 4: Feature Engineering (Slides; Python)
Lecture 5: Regularized Linear Models (Slides; Python)
Lecture 6: Generalized Additive Models (Slides; Python)
Lecture 7: Interpretable Machine Learning (Slides; Python)
Lecture 8: Tree-based Methods (Slides; Python)
Lecture 9: SVM, HyperOpt and AutoML (Slides; Python)
Lecture 10: Deep Neural Networks (Slides; Python)
Lecture 11: Explainable Neural Networks (Slides; Github)
Lecture 12: Unsupervised Learning (Slides)