https://web.stanford.edu/~hastie/ElemStatLearn/download.html
- https://www.kaggle.com/datasets
- http://archive.ics.uci.edu/ml/
- http://www.kdd.org/kdd-cup
- https://opendata.cityofnewyork.us/
Code in Google Colab for this semester: https://colab.research.google.com/
| Class | Sections to Read |
|---|---|
| 1 | 3.1-3.2.1, 3.3-3.4.3 |
| 2 | 4.1, 4.3 (not 4.3.1 and 4.3.2), 4.4-4.4.2 |
| 3 | part 2 section 5 --> http://cs229.stanford.edu/notes/cs229-notes1.pdf |
| 4 | Q&A + Code Review |
| 5 | 7.1, 7.2, 7.3, 7.10 |
| 6 | 9.2, https://arxiv.org/pdf/1603.02754v3.pdf, boosting: Sections 10.1, 10.6, 10.7, 10.9, 10.10 |
| 7 | https://medium.com/@gabrieltseng/gradient-boosting-and-xgboost-c306c1bcfaf5 |
| 8 | Q&A + Code Review |
| 9 | 15.1 - 15.3 |
| 10 | collab_filtering.pdf, matrixFactorization.pdf |
| 11 | ch 11 in machine_learning_in_action.pdf |
| 12 | code review and questions |
| 13 | code review and questions |
| 14 | code review and questions |
| 15 | code review and questions |