| Course Title: Applications of Machine Learning |
| Start Date: 09/04/2024 End Date: 12/17/2024 |
| Term: Fall Semester 2024 |
| Description: This course provides a practical and conceptual introduction to machine learning. Through programming projects and work with real-world data, we will study the motivations behind common machine learning algorithms, and the properties that determine whether or not they will work well for a particular task. We will also study practical applications of these algorithms to problems in areas such as speech, language, social sciences, and biology. Topics may include: supervised learning, classification, regression, clustering, decision trees, support vector machines, Naïve Bayes, neural networks and reinforcement learning. |
| Distribution(s): II - Math & Sciences |
| Academic Level Of Course: Undergraduate     | Credits:4.00     |
| Faculty         | Phone         | Email address         |
| Heather Pon-Barry   |           | ponbarry@mtholyoke.edu   |
| Meeting Dates         | Method         | Meeting days         | Meeting times         | Building name         | Room     | Frequency     |
| 09/04/2024 - 12/17/2024   | Lecture   | Tuesday and Thursday   | 10:30AM - 11:45AM   | KNDD - Kendade   | 203   | Weekly |
| Requisite Courses         | ||
| Prereq: COMSC-205. | Take previously   | Required   |
| Comments         |
| Additional Comments         |
| Course Tags         | ||
| DATA0003   | DATA-SE: Data Science Elective Course   | This course is an elective option for the Data Science major.   |
| NXDTA0001   | NXDTA: Nexus in Data Analytics and Society   | This course is approved for the Data Analytics   |
| Cross-listed Sections         |
| None   |
| Course Availability | ||||
| Section status: Closed     | Capacity: 18     | Enrollment: 18     | 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.   |