Lecture notes and code examples for MATH 6388: Statistical and Machine Learning
| Lecture | Description |
|---|---|
| Lecture 1 | Machine Learning Basics |
| Lecture 2 | Linear Regression, Optimization, and Regularization |
| Lecture 3 | Linear models for classification, loss function, and evaluation |
| Lecture 4 | Dense/convolutional neural networks, activation functions, and gradient descent |
| Lecture 5 | Conformal prediction |
| Lecture 6 | Clustering techniques |
| Lecture 7 | Dimensionality reduction techniques |