Machine Learning

Semester: 
Spring
Year: 
2019
Subject Name: 
Computer Science
Course Number: 
335
Institution: 
Mount Holyoke College
How does Neflix learn what movies a person likes? How do computers read handwritten addresses on packages, or detect faces in images? Machine learning is the practice of programming computers to learn and improve through experience, and it is becoming pervasive in technology and science. This course will cover the mathematical underpinnings, algorithms, and practices that enable a computer to learn. Topics will include supervised learning, unsupervised learning, evaluation methodology, and Bayesian probabilistic modeling. Students will learn to program in MATLAB or Python and apply course skills to solve real world prediction and pattern recognition problems. Programming Intensive.
Comments: 
Prereq: COMSC-211, MATH-232, and a Calculus course (MATH-101, MATH-102, or MATH-203).
Instructor Permission: 
Permission is required for interchange registration during all registration periods.
https://wadv1.mtholyoke.edu/wadvg/mhc?TYPE=P&PID=ST-XWSTS12A
Schedule #: 
106644

Course Sections

Machine Learning
Sect # Credits Instructor(s) Instructor Email Meeting Times Location
01 4.0 Daniel Sheldon dsheldon@mtholyoke.edu TTH 10:00AM-11:15AM Clapp Laboratory 206