| Course Title: Machine Learning |
| Start Date: 01/28/2025 End Date: 05/13/2025 |
| Term: Spring Semester 2025 |
| 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 |
| 01/28/2025 - 05/13/2025 | Lecture | Monday, Wednesday and Friday | 10:00AM - 11:15AM | KNDD - Kendade | 203 | Weekly |
| 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. |
| DATA0003 | DATA-SE: Data Science Elective Course | This course is an elective option for the Data Science major. |
| Cross-listed Sections |
| None |
| Course Availability | ||||
| Section status: Closed | Capacity: 18 | Enrollment: 20 | Available: 0 | 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. |