ECE398BD: Fundamentals of Machine Learning (Lectures)

Some lecture notes will be emailed to you.

Lecture 1 Introduction to the course; Review of linear algebra and probability
Lecture 2 k-Nearest Neighbor Classifiers and Bayes Classifiers
Lecture 3 Linear Classifiers and Linear Discriminant Analysis
Lecture 4 Kernel Tricks and Support Vector Machines
Lecture 5 Model Selection & Assessment and K-means clustering
Lecture 6 K-means Clustering (cont.) and Linear Regression
Lecture 7 SVD and Eigen-Decomposition
Lecture 8 SVD and Eigen-Decomposition (cont.)
Lecture 9 PCA and Applications, Q&A