Chapter 01: Would You Recommend to a Friend?
Lesson 01: Introduction: You, This Course & Us!
Lesson 02: What do Amazon and Netflix have in common?
Lesson 03: Recommendation Engines: a look inside
Lesson 04: What are you made of? Content-Based Filtering
Lesson 05: With a little help from friends: Collaborative Filtering
Lesson 06: A Model for Collaborative Filtering
Lesson 07: Top Picks for You! Recommendations with Neighborhood Models
Lesson 08: Discover the Underlying Truth: Latent Factor Collaborative Filtering
Lesson 09: Latent Factor Collaborative Filtering continued
Lesson 10: Gray Sheep & Shillings: Challenges with Collaborative Filtering
Lesson 11: The Apriori Algorithm for Association Rules
Chapter 02: Recommendation Systems in Python
Lesson 01: Installing Python : Anaconda & PIP
Lesson 02: Back to Basics: Numpy in Python
Lesson 03: Back to Basics: Numpy & Scipy in Python
Lesson 04: Movielens & Pandas
Lesson 05: Code Along: What’s my favorite movie? – Data Analysis with Pandas
Lesson 06: Code Along: Movie Recommendation with Nearest Neighbor CF
Lesson 07: Code Along: Top Movie Picks (Nearest Neighbor CF)
Lesson 08: Code Along: Movie Recommendations with Matrix Factorization
Lesson 09: Code Along: Association Rules with the Apriori Algorithm