Recipe
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Content Based Recommender Systems

Collaborators
Reviewers
Total time needed: ~2 hours
Learning Objectives
Compilation of learning materials
Potential Use Cases
Speed up your learning by finding topics aggregated in one place
Target Audience
BEGINNERBeginner Data Scientist/Machine Learning Engineer interested in learning the basics of content based recommender system
Go through the following annotated items in order:
BOOK_CHAPTER 1. Recommender Systems: The Textbook
  • What exactly is a content based recommender system?
  • What are some examples where they can be useful?
20 minutes
BOOK_CHAPTER 2. Recommender Systems: The Textbook
  • What is the importance of feature reduction and how can this be accomplished?
10 minutes
BOOK_CHAPTER 3. Recommender Systems: The Textbook
  • What are some examples of measures of discriminative power?
20 minutes
BOOK_CHAPTER 4. Recommender Systems: The Textbook
  • What models are useful in content based recommender systems?
30 minutes

Concepts Covered