Computer Science 589 - Machine Learning

Introduction to core machine learning models and algorithms for classification, regression, dimensionality reduction and clustering. The course will cover the mathematical foundations behind the most common machine learning algorithms, and the effective use in solving real-world applications. Requires a strong mathematical background and knowledge of one high-level programming language such as Python.

Sr & Jr CS majors with a grade of C or better in MATH 545, STAT 515, & CS 240; OR a C or better in MATH 545 and B+ or better in CS 240; OR a C or better in STAT 515 & CS 240 and B+ or better in MATH 233 & 235; OR B+ or better in CS 240, MATH 233 and 235. LECT 01 FOR UNDERGRADS; LECT 02 FOR ELIGIBLE GRADS; SEATS HELD FOR INCOMING GRAD STUDENT REGISTRATION. UWW LECT 01 FOR ONLINE MS-CMPSCI PROGRAM STUDENTS ONLY. PHDS OR ANY STUDENT WITH A TUITION WAIVER CANNOT ENROLL IN A UWW SECTION. UNIV SECTIONS -01 AND -02 MEET IN PERSON ON THE AMHERST CAMPUS WITH THE INSTRUCTOR TEACHING REMOTELY FROM THE MT. IDA CAMPUS. TA'S WILL BE AVAILABLE IN THE AMHERST CLASSROOM. STUDENTS NEEDING SPECIAL PERMISSION MUST REQUEST OVERRIDES VIA THE ON-LINE FORM: https://www.cics.umass.edu/overrides.