| Call Number | 13650 |
|---|---|
| Day & Time Location |
F 6:10pm-8:40pm 717 Hamilton Hall |
| Points | 3 |
| Grading Mode | Standard |
| Approvals Required | None |
| Instructor | Parijat Dube |
| Type | LECTURE |
| Method of Instruction | In-Person |
| Course Description | Prerequisites: STAT GR5206 or the equivalent. The course will provide an introduction to Machine Learning and its core models and algorithms. The aim of the course is to provide students of statistics with detailed knowledge of how Machine Learning methods work and how statistical models can be brought to bear in computer systems - not only to analyze large data sets, but to let computers perform tasks that traditional methods of computer science are unable to address. Examples range from speech recognition and text analysis through bioinformatics and medical diagnosis. This course provides a first introduction to the statistical methods and mathematical concepts which make such technologies possible. |
| Web Site | Vergil |
| Department | Statistics |
| Enrollment | 60 students (86 max) as of 9:14PM Wednesday, November 20, 2024 |
| Subject | Statistics |
| Number | GR5241 |
| Section | 001 |
| Division | Interfaculty |
| Open To | GSAS |
| Section key | 20241STAT5241W001 |