ECE 6254 - Lectures

May 11, 2020 Lecture 1 - Supervised Learning Framework
May 13, 2020 Lecture 2 - Probably Approximately Correct Learnability
May 18, 2020 Lecture 3 - Bayes and Nearest Neighbors Classifiers
May 20, 2020 Lecture 4 - Plugin classifiers
May 27, 2020 Lecture 5 - Logistic regresssion, Descent Algorithms
Jun 01, 2020 Lecture 6 - Perceptron Learning Algorithm
Jun 03, 2020 Lecture 7 - Kernel methods and convex optimization
Jun 08, 2020 Lecture 8 - Kernel methods and convex optimization
Jun 10, 2020 Lecture 9 - #ShutDownSTEM #BlackLivesMatter
Jun 15, 2020 Lecture 10 - Introduction to VC dimension
Jun 17, 2020 Lecture 11 - Introduction to VC dimension (part 2)
Jun 22, 2020 Lecture 12 - Introduction to VC dimension (part 3)
Jun 24, 2020 Lecture 13 - Regression and Regularization
Jun 29, 2020 Lecture 14 - Regression and Regularization II
Jul 01, 2020 Lecture 15 - Bias-Variance Tradeoff and Model selection
Jul 06, 2020 Lecture 16 - Dimensionality reduction
Jul 08, 2020 Lecture 17 - Multi-dimensional scaling
Jul 13, 2020 Lecture 18 - Kernel density estimation and Clustering
Jul 15, 2020 Lecture 19 - Kernel methods
Jul 20, 2020 Lecture 20 - Representer theorem
Jul 20, 2020 Lecture 21