Section Info: COMSC-335-01

Course Title: Machine Learning
Start Date: 08/24/2020 End Date: 10/15/2020
Term: Fall Semester 2020
Description: How does Netflix 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.
Distribution(s): II - Math & Sciences
Academic Level Of Course: Undergraduate     Credits:4.00    

Faculty         Phone         Email address        
Melody Su             msu@mtholyoke.edu  

Meeting Dates         Method         Meeting days         Meeting times         Building name         Room     Frequency    
08/24/2020 - 10/15/2020   Flex. Immersive Lecture   Monday   08:00AM - 09:15AM   TBA   TBA   Weekly
08/24/2020 - 10/15/2020   Flex. Immersive Lecture   Tuesday and Thursday   08:00AM - 09:00AM       Weekly
08/24/2020 - 10/15/2020   Flex. Immersive Lecture   Wednesday and Friday   08:00AM - 09:45AM       Weekly

REGISTRATION DETAILS

Requisite Courses        
Prereq: A grade of C or better in COMSC-205, MATH-232, and a Calculus course (MATH-101, MATH-102, or MATH-203). Take previously   Required  

Comments        
Additional Comments        
Course Tags        
NXDTA0001   NXDTA: Nexus in Data Analytics and Society   This course is approved for the Data Analytics  
DATA0001   DATA-SCI: Data Science Core Course   This is a required core course of the Data Science major.  
MOD0001   MOD-1: Courses meeting in Module 1   This course meets in Module 1.  

Cross-listed Sections        
None  

Course Availability
Section status: Open     Capacity: 18     Enrollment: 16     Available: 2     Waitlist: 0

BOOK INFORMATION

Book List         Required         Publisher Full Price        
To be determined.                    

Additional Book Comments        
This is NOT the complete book list for this class.