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 |
|---|---|---|---|---|---|---|---|---|---|
| 31529D | 048 | Lecture | 2:00-3:50pm | Mon, Wed | 0 of 45 | OHE122 |  | ||
| 31546D | 048 | Lecture | 2:00-3:50pm | Tue, Thu | 0 of 49 | GFS101 | | ||
| 31712D | 048 | Lecture | 5:30-7:20pm | Mon, Wed | 0 of 70 | Tao Ma | SOSB46 | | |
| 31729D | 048 | Lecture | 5:30-7:20pm | Tue, Thu | 0 of 90 | GFS106 | | ||
| 31731D | 034 | Lecture | 2:00-3:50pm | Mon, Wed | 0 of 20 | DEN@Viterbi | |