Industrial and Systems Engineering 529:
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.
Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
---|---|---|---|---|---|---|---|---|---|
31529D | 048 | Lecture | 2:00-3:50pm | Mon, Wed | 45 of 45 | Maryam Pishgar | OHE122 | PDF (146581 KB) | |
31546D | 048 | Lecture | 2:00-3:50pm | Tue, Thu | 37 of 60 | Tao Ma | ZHS163 | PDF (145174 KB) | |
31726D | 048 | Lecture | 5:30-7:20pm | Tue, Thu | 33 of 90 | Tao Ma | SOSB2 | PDF (144688 KB) | |
31729D | 048 | Lecture | 12:00-1:50pm | Mon, Wed | 40 of 40 | Maryam Pishgar | VHE217 | PDF (145287 KB) | |
31731D | 034 | Lecture | 2:00-3:50pm | Mon, Wed | 6 of 20 | Maryam Pishgar | DEN@Viterbi | PDF (146581 KB) |