Foundations of Machine Learning


Foundations of Machine Learning

MET CS 555 (4 credits)

Formerly titled CS 555 Data Analysis and Visualization with R.
This course provides an overview of the statistical tools most commonly used to process, analyze, and visualize data. Topics include simple linear regression, multiple regression, logistic regression, analysis of variance, and survival analysis. These topics are explored using the statistical package R, with a focus on understanding how to use and interpret output from this software as well as how to visualize results. In each topic area, the methodology, including underlying assumptions and the mechanics of how it all works along with appropriate interpretation of the results, are discussed. Concepts are presented in context of real world examples. Recommended Prerequisite: MET CS 544 or equivalent knowledge, or instructor's consent.

2022FALLMETCS555 A1, Sep 12th to Dec 12th 2022

Days Start End Type Bldg Room
M 06:00 PM 08:45 PM EPC 208

2022FALLMETCS555 A2, Sep 8th to Dec 8th 2022

Days Start End Type Bldg Room
R 06:00 PM 08:45 PM MET 122

2022FALLMETCS555 A3, Sep 8th to Dec 8th 2022

Days Start End Type Bldg Room
R 09:00 AM 11:45 AM MET 122

2022FALLMETCS555 O2, Nov 1st to Dec 19th 2022

Days Start End Type Bldg Room
ARR TBD TBD ROOM

2023SPRGMETCS555 A1, Jan 24th to May 2nd 2023

Days Start End Type Bldg Room
T 12:30 PM 03:15 PM CAS B36

2023SPRGMETCS555 A2, Jan 19th to Apr 27th 2023

Days Start End Type Bldg Room
R 12:30 PM 03:15 PM MET 122

2023SPRGMETCS555 A3, Jan 19th to Apr 27th 2023

Days Start End Type Bldg Room
R 06:00 PM 08:45 PM CAS 216

2023SPRGMETCS555 O1, Jan 17th to Mar 6th 2023

Days Start End Type Bldg Room
ARR TBD TBD ROOM

Format & Syllabus: