| Event Type | Date | Description | Course Materials |
|---|---|---|---|
| Lecture | April 4, 2017 | Logistics | |
| Lecture | April 6, 2017 | Introduction to Machine Learning | [Intro to Machine Learning Slides] |
| Lecture | April 11, 2017 | Probablity, Linear Algebra, Linear Regression |
[Probability Slides] [Linear Algebra Slides] [Linear Regression Slides] |
| Lecture | April 13, 2017 | Linear Regression |
[Linear Regression Slides] [Matrix Calculus Reference] |
| Lecture | April 15, 2017 | No Class, Faculty Lecture | |
| Lecture | April 18, 2017 | Linear Regression, Logistic Regression |
[Linear Regression Slides] [Logistic Regression Slides] [Andrew Ng's Lecture Notes] |
| Lecture | April 20, 2017 | Generative -vs- Discriminative Models, GDA, Naive Bayes |
[Generative -vs- Discriminative Slides] [GDA and Naive Bayes Slides] [Andrew Ng's Lecture Notes] |
| Lecture | April 22, 2017 | Kevin out of town, Daniel will lead project discussion | |
| Lecture | April 27, 2017 | iPython Notebooks, Scikit-Learn, GDA, QDA, Logistic Regression, and Linear Regression Examples | |
| Lecture | May 2, 2017 | Decision Trees and their Ensembles | |
| Lecture | May 4, 2017 | Neural Networks |
[Neural Net Slides] |
| Lecture | May 9, 2017 | Model Assessment: ROC Curves, Confusion Matrices, F1Score |
[Model Assessment Slides] |
| Lecture | May 11, 2017 | Linear Dimensionality Reduction: PCA and SVD |
[Dimensionality Reduction Slides] |
| Lecture | May 16, 2017 | Nonlinear Dimensionality Reduction | |
| Lecture | May 18, 2017 | Guest Lecture: Nonconvex Optimization | |
| Lecture | May 23, 2017 | Clustering | |
| Lecture | May 25, 2017 | Model Selection and Hyperparameter Tuning | |
| Lecture | May 30, 2017 | Cross-Validation, Model Selection, and Hyperparameter Tuning | |
| Lecture | June 1, 2017 | SVMs | |
| Lecture | June 6, 2017 | Project Presentations | |
| Lecture | June 8, 2017 | Project Presentations |
