CSE 176: Introduction to Machine Learning
Units: 4
Survey of techniques for development and analysis of software that learns from experience. Specific topics: supervised learning (classification, regression); unsupervised learning (density estimation, clustering, dimensionality reduction); reinforcement learning; and others. Specific techniques: linear classifiers, mixture models, nonparametric methods, decision trees, neural networks, kernel machines, ensembles, graphical models, Bayesian methods, etc.
Course Details
Repeats Allowed for Credit: 0
Laboratory included
Normal Letter Grade only
GE Requirements - Badge: Quantitative and Numerical Analysis
- Badge: Scientific Method
- Upper Division: Crossroads
Requisites and Restrictions
Prerequisite Courses: CSE 031 and CSE 100 and MATH 141
Open only to the following class level(s):
Instructor Permission Required: No
View course scheduling information
Add to My Catalog (opens a new window)
|
