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  3. Building Recommendation Engines in Python

Exercise

Finding similarly liked movies

Just like you calculated the similarity between two movies, you can calculate it across all users to find the most similar movie to another based on how users have rated them.

The approach is similar to how you worked with content-based filtering.

You will find the similarity scores between all movies and then drill down on the movie of interest by isolating and sorting the column containing its similarity scores.

movie_ratings_centered has once again been loaded, containing each movie as a row, and their centered ratings stored as the values.

Instructions

100 XP
  • Calculate the similarity matrix between all movies in movie_ratings_centered and store it as similarities.
  • Wrap the similarities matrix in a DataFrame, with the indices of movie_ratings_centered as the columns and rows.