ECE398BD: Fundamentals of Machine Learning (Lectures)

You can find the typed notes for this class [here]. The course follows essentially linearly with the notes.

	Topic	Quiz
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	Naive Bayes and Kernel Tricks	Quiz 1, 4:30 PM
Lecture 5	Logistic Regression, Support Vector Machines and Model Selection
Lecture 6	K-means Clustering	Quiz 2, 4:30 PM
Lecture 7	Linear Regression
Lecture 8	SVD and Eigen-Decomposition
Lecture 9	Principal Component Analysis
Lecture 10	Optimization Methods for Machine Learning, Q&A

Useful links: