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Course on Recommender Systems conducted at the Faculty of Computer Science, National Research University - Higher School of Economics. Academic year 2024/2025.

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RecSys course

The course on recommender systems conducted in National Research University - Higher School of Economics (Moscow, Russia). Academic year 2024/2025.

Useful Links

  • Wiki page of this course
  • Table with grades
  • The code materials for each seminars can be found in the corresponding folders /seminar*.
  • To download any folder please use this link.
  • Recordings of lectures and seminars (coming soon).
  • All questions can be asked in the Telegram chat (the invitation link is available only to NRU HSE students)

The most important section

The final grade is calculated as follows:

0.3 * Home Assignment + 0.3 * Quizzes + 0.4 * Exam

where Home Assignments - 5 home assignments in Jupyter Notebook (max 10 points). Quizzes - 19 weekly quizzes on lecture's and seminars' topics in Google Forms (max 10 points). Exam - oral examination on all topics (max 10 points).

Course outline

  1. Introduction to recommender systems
  2. Similarity (neighborhood) based and linear approaches
  3. Matrix factorization
  4. Collaborative filtering
  5. Content-based models
  6. Hybrid approaches
  7. Sequential models for next-item recommendations
  8. Context-based recommendations
  9. Models for the next-basket recommendations task
  10. Autoencoders and variational autoencoders for recommendations
  11. Graph and knowledge-graph based models
  12. Interpretability and explainability
  13. Uplift recommendations
  14. Multi-task & cross-domain recommendations
  15. RL in RecSys
  16. Domain recommendations (multiomodal data)
  17. A/B testing and multi-armed bandites. Model monitoring
  18. Large scale RecSys
  19. Vanilla API service for recommender system
  20. Additional applied aspects and trends in recommender systems

Contributors

License

All content created for this course is licensed under the MIT License. The materials are published in the public domain.

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Course on Recommender Systems conducted at the Faculty of Computer Science, National Research University - Higher School of Economics. Academic year 2024/2025.

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