Week 2: Recommender Systems

Learning Objectives

• Implement collaborative filtering recommender systems in TensorFlow

• Implement deep learning content based filtering using a neural network in TensorFlow

• Understand ethical considerations in building recommender systems

Collaborative filtering

Making recommendations - Video • Duration: 5 min

Using per-item features - Video • Duration: 11 min

Collaborative filtering algorithm - Video • Duration: 13 min

Binary labels: favs, likes and clicks - Video • Duration: 8 min

Practice quiz: Collaborative filtering

Collaborative Filtering

Practice lab 1

Collaborative Filtering Recommender Systems

Recommender systems implementation

Mean normalization - Video • Duration: 8 min

TensorFlow implementation of collaborative filtering - Video • Duration: 11 min

Finding related items - Video • Duration: 6 min

Practice quiz Recommender systems implementation

Recommender systems implementation

Content-based filtering

Collaborative filtering vs Content-based filtering - Video • Duration: 9 min

Deep learning for content-based filtering - Video • Duration: 9 min

Recommending from a large catalogue - Video • Duration: 7 min

Ethical use of recommender systems - Video • Duration: 10 min

TensorFlow implementation of content-based filtering - Video • Duration: 4 min

Practice Quiz: Content-based filtering

Content-based filtering

Practice lab 2

Deep Learning for Content-Based Filtering