RecSysCourse 2020 - Master Foundation of Data Science

University of Barcelona

Recommender Systems Repository

This repository contains notebooks used in RECOMMENDER SYSTEMS COURSE of the MASTER OF FUNDATIONS IN DATA SCIENCE at the Universitat de Barcelona.

Course Description

This course will cover the basics of recommender systems by using a hands-on approach.

Course Instructor

Santi Seguí

Class Time and Location

2nd Semester (February - May, 2020) Lecture: Thursday 15:00-17:00 Location: Aula B1, Facultat de Matemàtiques i Informàtica, Universitat de Barcelona

Prerequisites

• Proficiency in Python: All class assignments will be in Python
• Calculus, Linear Algebra, Optimization
• Basic Probability and Statistics.
• Machine Learning.

Grading

• Assignment #1 - Code Delivery: 25%
• Assignment #2 - Code Delivery: 25%
• Assignment #3 - Presentations: 25%
• Final Examen: 25%

Study groups are allowed but we expect students to understand and complete their own assignments and to hand in one assignment per student.

Course Agenda

1. Feb, 13: Introduction to Recommender Systems.
2. Feb, 20: Non-Personalized Recommenders.
3. Feb, 27: Collaborative-Based Recommender Systems.
4. March, 5: Collaborative-Based Recommender Systems.
5. March, 12: Dimensionaly Reduction for Recommender Systems.
6. March, 19: Content-Based Recommender Systems.
7. March, 26: RecSys Challenge.
8. April, 2: RecSys Challenge
9. April, 9: NO CLASS - Easter Break
10. April, 16: Evaluation/Graph-Based Models
11. April, 23: NO CLASS -
12. April, 30: Deep Learning Models
13. May, 7: Context Based Models
14. May, 14: Group Based Models / Knowledge Recommendations
15. May, 21: Current Practices in Industry and Research
16. May, 28: EXAM