Building a Basic Collaborative Filtering Recommender with Python
import numpy as np def compute_pair_similarity(vec_a, vec_b): shared_mask = (vec_a > 0) & (vec_b > 0) if shared_mask.sum() == 0: return 0.0 a = vec_a * shared_mask b = vec_b * shared_mask return np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b)) def generate_suggestions(target_user, sc...