Mathematics 447:
Mathematics of Machine Learning (4.0 units)
Mathematical aspects of Machine Learning. PAC Learning, VC-dimension and complexity. Linear predictors (regression, perceptron, SVM). Convex learning and gradient descent. Neural networks and backpropagation.
- Prerequisite: 1 from (MATH 226 or MATH 227 or MATH 229) and 1 from (MATH 208 or MATH 407) and 1 from (MATH 225 or MATH 245)
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 39676D | 001 | Lecture | 2:00-2:50pm | MWF | 15 of 40 | Guillermo Reyes Souto | KAP163 | PDF (58592 KB) |  |