Schedule (Fall 2024)

Lectures

Introduction to CSC 461 [Slides]
- Readings: Google's Python Class [WEB], Numpy Tutorial [WEB]
Machine Learning Basics [Slides]
- Readings: Introduction (DL Book) [PDF]
Math/Python Preliminaries [Slides]
- Readings: Linear Algebra (DL Book) [PDF], Numpy Broadcasting [WEB]
Clustering, K-Means [Slides] [Colab]
- Readings: Chapter 4 [PDF]
Hierarchical Clustering [Slides] [Colab]
- Readings: Section 22.1 [PDF]
PCA [Slides] [Colab 1] [Colab 2]
- Readings: Section 23.1 [PDF]
Supervised Learning [Slides] [Colab]
- Readings: Chapters 2 and 3 [PDF]
k-Nearest Neighbors [Slides]
- Readings: Chapter 19 [PDF]
Model Selection [Slides] [Colab]
- Readings: Chapter 11 [PDF]
Decision Trees I [Slides]
- Readings: Chapter 18 [PDF]
Decision Trees II [Slides] [Colab]

topics for midterm exam end here