Building a movie recommendation system

So far, we have laid the foundation to build our recommendation system by learning about:

• Extracting the nearest neighbors
• Building a K-nearest neighbors classifier
• Computing similarity scores
• Finding similar users using collaborative filtering

Now that all the building blocks in place, it's time to build a movie recommendation system. We learned all the underlying concepts that are needed to build a recommendation system. In this section, we will build a movie recommendation system based on the data provided in the file ratings.json. This file contains a set of people and their ratings for various movies. To find movie recommendations for a given user, we need to find similar users in the dataset and then come up with recommendations for this person. Let's get started.

Create a new Python file and import the following packages:

import argparse
import json
import numpy as np

from compute_scores...