Python Machine Learning Cookbook

Finding similar users in the dataset

One of the most important tasks in building a recommendation engine is finding users that are similar. This guides in creating the recommendations that will be provided to these users. Let's see how to build this.

How to do it…

1. Create a new Python file, and import the following packages:

   import json
   import numpy as np
   
   from pearson_score import pearson_score

2. Let's define a function to find similar users to the input user. It takes three input arguments: the database, input user, and the number of similar users that we are looking for. Our first step is to check whether the user is present in the database. If the user exists, we need to compute the Pearson correlation score between this user and all the other users ...