(Matrix Factorizations and Recommender Systems)
Goals. The goal of this exercise is to
• Build a recommender system.
• Learn to evaluate its performance.
• Implement and understand matrix factorization using SGD.
• Implement and understand the alternating least-squares (ALS) algorithm.
Setup, data and sample code. Obtain the folder labs/ex13 of the course github repository
github.com/epfml/ML course/tree/master/labs/ex13
You can also the notebook in Google Colab:
colab.research.google.com/github/epfml/ML course/tree/master/labs/ex13/template/ex13.ipynb
1 Notebook
The notebook guides you through data preparation, the design of baselines, and the implementation and training of a Matrix Factorization algorithm for recommendation.
