Introduction to Machine Learning

Description: (Same as Electrical Engineering M146.) Lecture, four hours; discussion, one hour; outside study, seven hours. Requisites: Civil and Environmental Engineering 110 or Electrical Engineering 131A or Mathematics 170A or Statistics 100A, course 33. Introduction to breadth of data science. Foundations for modeling data sources, principles of operation of common tools for data analysis, and application of tools and models to data gathering and analysis. Topics include statistical foundations, regression, classification, kernel methods, clustering, expectation maximization, principal component analysis, decision theory, reinforcement learning and deep learning. Letter grading.

Units: 4.0
1 of 1
Overall Rating 3.6
Overall Rating N/A
Easiness N/A/ 5
Clarity N/A/ 5
Workload N/A/ 5
Helpfulness N/A/ 5
1 of 1

Adblock Detected

Bruinwalk is an entirely Daily Bruin-run service brought to you for free. We hate annoying ads just as much as you do, but they help keep our lights on. We promise to keep our ads as relevant for you as possible, so please consider disabling your ad-blocking software while using this site.

Thank you for supporting us!