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Recommender Systems course for MIPT IDA 4th-year students

recsys-course 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# Welcome to MIPT 2026 Recommender Systems course

## Description

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.

## The Syllabus

| Lecture | Date | Description | Materials | Video |
| ------- | ------------ | -------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------- | ------------------------------------------------- |
| 1 | February, 24 | Introduction ([A. Grishanov](https://github.com/shashist)) | [slides](https://nbviewer.org/github/shashist/recsys-course/blob/main/week_01_introduction/rs_lecture01.pdf) | [video](https://www.youtube.com/live/aSxLu8863fI) |
| 2 | March, 3 | Neighborhood-Based models ([A. Grishanov](https://github.com/shashist)) | [slides](https://nbviewer.org/github/shashist/recsys-course/blob/main/week_02_neighbourhood_based/rs_lecture02.pdf) [notebook](https://nbviewer.org/github/shashist/recsys-course/blob/main/week_02_neighbourhood_based/rs_seminar1.ipynb) | [video](https://youtu.be/okpEcNe1-f8) |
| 3 | March, 10 | Matrix Factorization models ([A. Grishanov](https://github.com/shashist)) | [slides](https://nbviewer.org/github/shashist/recsys-course/blob/main/week_03_matrix_factorization/rs_lecture03.pdf) | [video](https://www.youtube.com/live/m426XhlRPoA?si=Sj_Gjp4eV0B9wPtl) |
| 4 | March, 17 | Content-based and Hybrid systems ([A. Grishanov](https://github.com/shashist)) | [slides](https://nbviewer.org/github/shashist/recsys-course/blob/main/week_04_hybrid/rs_lecture04.pdf) | [video](https://www.youtube.com/live/zGzLR76Le2Q) |
| 5 | March, 24 | Neural recommenders ([A. Grishanov](https://github.com/shashist)) | [slides](https://github.com/shashist/recsys-course/blob/main/week_05_neural_recommenders/rs_lecture05.pdf) | [video](https://www.youtube.com/live/D82dz9h6cOI?si=F6xS0CgVsgvJVF0n) |
| 6 | April, 7 | Two-level models ([A. Grishanov](https://github.com/shashist)) | [notebook](https://github.com/shashist/recsys-course/blob/main/week_06_two-level/rs_seminar_2-level.ipynb) | [video](https://youtube.com/live/u-q792ePM6g) |
| 7 | April, 14 | Multi-armed bandits ([A. Grishanov](https://github.com/shashist)) | [slides](https://github.com/shashist/recsys-course/blob/main/week_07_bandits/rs_lecture07.pdf) | [video](https://www.youtube.com/live/ySkxuNU3oYI) |
| 8 | April, 21 | Counterfactual evaluation ([A. Grishanov](https://github.com/shashist)) | [slides](https://github.com/shashist/recsys-course/blob/main/week_08_counterfactual/rs_lecture08.pdf) | [video](https://www.youtube.com/watch?v=EnOL11l7JmQ) |

## Homeworks

| Homework | Date      | Deadline  | Description | Link                                  |
| -------- |-----------|-----------| ----------- |---------------------------------------|
| 1        | April, 28 | May, 19 |  theoretical  | [link](homeworks/hw_bandits/rs_hw_bandits_en.pdf) |
| 2        | May, 22 | May, 23 | practical | [notebook](homeworks/hw_als/hw_als.ipynb) |

#### Grade = `min(round(2*hw1_points + hw2_points), 10)`

## Additional materials
* [single-lecture course overview (in Russian)](https://www.youtube.com/watch?v=jEzNbEc7DFE) - overview lecture with Q&A, 2025
* ["Recommender systems and RePlay library" course (in Russian)](https://sberuniversity.ru/learning/course/rekomendatelnye-sistemy-i-biblioteka-replay) - friendly course from https://github.com/sb-ai-lab/RePlay team

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