Course objective is to provide comprehensive introduction to the field of Recommender Systems.
- first part of the course is dedicated to general RecSys approaches
- second part briefly covers multi-armed bandits and counterfactual evaluation
To join this course contact https://t.me/alexey_grishanov.
| Lecture | Date | Description | Materials | Video |
|---|---|---|---|---|
| 1 | February, 13 | Introduction (A. Grishanov) |
slides | video |
| 2 | February, 20 | Neighborhood-Based models (A. Grishanov) |
slides notebook | video |
| 3 | February, 27 | Matrix Factorization models (A. Volodkevich) |
slides notebook | video |
| 4 | March, 5 | Content-based and Hybrid systems (A. Volodkevich) |
slides | video |
| 5 | March, 12 | Two-level models (A. Grishanov) |
notebook | video |
| 6 | March, 19 | Neural recommenders (A. Volodkevich) |
slides notebook | video |
| 7 | March, 26 | Multi-armed bandits (A. Grishanov) |
slides | video |
| 8 | April, 2 | Counterfactual evaluation (A. Grishanov) |
slides | video |
| 9 | April, 9 | Next-Basket Recommendations (guest lecture by O. Lashinin) |
slides | video |
| Homework | Date | Deadline | Description | Link |
|---|---|---|---|---|
| 1 | March, 13 | March, 27 | practical | link |
| 2 | April, 28 | May, 12 | theoretical | link |