CS4602 Introduction to Machine Learning

Content

Lecture 1: Introduction and Basic Concepts
Lecture 2: Regression

Regression vs Classification | Linear regression | Overfitting and regularization | Autoregression | Logistic regression (more like classification)

Assignment 1 Systolic Blood Pressure Prediction

Basic Implementation | Advanced Implementation

Lecture 3: Bayesian Classifiers
Assignment 2 Hospital Death and Diabetes Mellitus Classification

Basic Implementation | Advanced Implementation

Lecture 4: Decision Trees (Bagging and Boosting)
Lecture 5: Linear Classifiers

Perceptron Algorithm | Least-Squares Classifiers | Fisher's Linear Discriminant | Support Vector Machines

Lecture 6: Neural Networks

Motivation | Multilayer perceptrons (MLP) | Backpropogation

Lecture 7: Deep Learning

Lecture 8: CNN/RNN