Raspberry Pi 3 Cookbook for Python Programmers - Third Edition

How to do it...

1. We will create a new Python file and import the following packages:

import json 
import numpy as np 
from euclidean_score import euclidean_score 
from pearson_score import pearson_score 
from search_similar_user import search_similar_user

2. For movie recommendations for a given user, we will define a function first. We now check whether the user already exists:

# Generate recommendations for a given user 
def recommendation_generated(dataset, user): 
if user not in dataset: 
raiseTypeError('User ' + user + ' not present in the dataset') 

3. Compute the person score for the present user:

sumofall_scores= {} identical_sums= {} for u in [x for x in dataset if x != user]: identical_score= pearson_score(dataset, user, u) if identical_score<= ...