100% Plagiarism-Free
+1-727-416-5453

Sign In

Access your dashboard and order activity.

Forgot password?

Create Account

Register to place orders and track every step.

COMP SCI 561

Probability and Information Theory in Machine Learning

University of Wisconsin-Madison 3 credits COMP SCI

Course Description

Probabilistic tools for machine learning and analysis of real-world datasets. Introductory topics include classification, regression, probability theory, decision theory and quantifying information with entropy, relative entropy and mutual information. Additional topics include naive Bayes, probabilistic graphical models, discriminant analysis, logistic regression, expectation maximization, source coding and variational inference.

Code
COMP SCI 561
Credits
3
Subject
COMP SCI

Programs That Include This Course

Get expert help with COMP SCI 561 Probability and Information Theory in Machine Learning

Our subject experts help with essays, research papers, case studies, discussion posts, and capstone projects for these programs β€” written from scratch to your course requirements.

Get Help Now

Program and course information is reproduced from each university's published academic catalog for informational purposes and may change. Always confirm current requirements with your university. We are an independent academic support service and are not affiliated with or endorsed by the universities listed.

Academic Resources

Latest from the Blog

Expert guides on essay writing, citation styles, study skills, and academic success.

View All Articles