Exercise

The recommender function

In this exercise, we will build a recommender function get_recommendations(), as discussed in the lesson and the previous exercise. As we know, it takes in a title, a cosine similarity matrix, and a movie title and index mapping as arguments and outputs a list of 10 titles most similar to the original title (excluding the title itself).

You have been given a dataset metadata that consists of the movie titles and overviews. The head of this dataset has been printed to console.

Instructions

100 XP

Get index of the movie that matches the title by using the title key of indices.
Extract the ten most similar movies from sim_scores and store it back in sim_scores.