- 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
- 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')
- 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<= ...