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 |