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, 24 | Introduction (A. Grishanov) |
slides | video |
| 2 | March, 3 | Neighborhood-Based models (A. Grishanov) |
slides notebook | video |
| 3 | March, 10 | Matrix Factorization models (A. Grishanov) |
slides | video |
| 4 | March, 17 | Content-based and Hybrid systems (A. Grishanov) |
slides | video |
| 5 | March, 24 | Neural recommenders (A. Grishanov) |
slides | video |
| 6 | April, 7 | Two-level models (A. Grishanov) |
notebook | video |
| 7 | April, 14 | Multi-armed bandits (A. Grishanov) |
slides | video |
| 8 | April, 21 | Counterfactual evaluation (A. Grishanov) |
slides | video |
| Homework | Date | Deadline | Description | Link |
|---|---|---|---|---|
| 1 | April, 26 | May, 10 | practical | TBA |
| 2 | May, 11 | May, 25 | theoretical | TBA |
- 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