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)