Data Science 561:
Predictive Analytics (4.0 units)
Supervised learning. Linear regression, cross validation, ridge and lasso regression, logistic regression, k-nearest-neighbors, decision trees, random forest and gradient-boosting models, support vector machines, neural networks.
- Crosslist: This course is offered by the ISE department but may qualify for major credit in DSCI. To register, enroll in ISE 529.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31546D | 048 | Lecture | 12:00-1:50pm | Mon, Wed | 40 of 40 | Maryam Pishgar | OHE100D | PDF (166985 KB) |  |
| 31729D | 048 | Lecture | 12:00-1:50pm | Tue, Thu | 26 of 30 | Victoria Stodden | GER206 | | |
| 31731D | 048 | Lecture | 4:00-5:50pm | Tue, Thu | 43 of 65 | Victoria Stodden | THH208 | | |
| 31746D | 034 | Lecture | 12:00-1:50pm | Mon, Wed | 2 of 20 | Maryam Pishgar | DEN@Viterbi | PDF (166985 KB) | |