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, 18 | Introduction (A. Grishanov) |
slides | video |
| 2 | February, 25 | Neighborhood-Based models (A. Grishanov) |
slides notebook | video |
| 3 | March, 4 | Matrix Factorization models (A. Volodkevich) |
slides notebook | video |
| 4 | March, 11 | Content-based and Hybrid systems (A. Volodkevich) |
slides | video |
| 5 | March, 18 | Two-level models (A. Grishanov) |
notebook | video |
| 6 | March, 25 | Neural recommenders (A. Volodkevich) |
slides notebook | video |
| 7 | April, 1 | Multi-armed bandits (A. Grishanov) |
slides | video |
| 8 | April, 8 | Counterfactual evaluation (A. Grishanov) |
slides | video |
| Homework | Date | Deadline | Description | Link |
|---|---|---|---|---|
| 1 | March, 11 | March, 25 | practical | notebook |
| 2 | April, 8 | April, 22 | theoretical | link |
- single-lecture course overview (in Russian) - overview lecture with Q&A, 2025
- "Recommender systems and RePlay library" course (in Russian) - friendly course from https://github.com/sb-ai-lab/RePlay team