Movie Recommendation System: Code Snippets

import numpy as np

def predict_score(user_vec, item_vec, user_bias=0.0, item_bias=0.0, global_bias=3.2):
    dot = np.dot(user_vec, item_vec)
    return global_bias + user_bias + item_bias + dot

def top_n_recommendations(user_id, user_matrix, item_matrix, n=10):
    scores = []
    for item_id, item_vec in enumerate(item_matrix):
        score = predict_score(user_matrix[user_id], item_vec)
        scores.append((item_id, score))
    scores.sort(key=lambda x: x[1], reverse=True)
    return scores[:n]