Recommender Systems (2235.YR.008019.1)

General information

Type:	OPT	Curs:	1	Period:	S semester
ECTS Credits:	3 ECTS

Teaching Staff:

Group	Teacher	Department	Language
Year 1	Marc Torrens Arnal	Operaciones, Innovación y Data Sciences	ENG

None

- Basic Pyhton programming skills

Recommender Systems are probably the most commercial application of Machine Learning. This course is about learning the main algorithm families to build scalable and data-driven recommender systems for commercial applications such as electronic commerce.

The main objective of the course is to learn the main algorithms and techniques to develop Recommender Systems that are widely used in the Internet industry. Students will learn the main aspects surrounding Recommender Systems including algorithms, evaluation, implementation, and business implications.

1. Introduction to Recommender Systems

2. Recommendation Methods

3. Collaborative Filtering

4. Content-based filtering

5. Building a recommendation engine in the real world

6. Final project preparation

7. Final project presentation

- Recommender Systems Handbook. Lior Rokach, Bracha Shapira, Francesco Ricci.
- Coursera: Recommender Systems Specialization. University of Minnesota.

Group	Teacher	Department
Year 1	Marc Torrens Arnal	Operaciones, Innovación y Data Sciences