CS 341 - Machine Learning

Credits: 4

This course will introduce the fundamental concepts, algorithms, and theories in machine learning and their practical application to real problems. This course will introduce supervised learning (decision trees, logistic regression, support vector machines, Bayesian methods, neural networks and deep learning), unsupervised learning (clustering, dimensionality reduction). reinforcement learning as well as introduction to deep learning. Various examples and applications will also be discussed.

Pre-Requisites: CS 231 or CS 340
Repeatable: May not be repeated for credit
Lecture: 2
Lab: 2