codsoft_task4 Recommendation System

import pandas as pd from sklearn.metrics.pairwise import cosine_similarity

data = { 'User': ['User1', 'User2', 'User3', 'User4', 'User5'], 'Book1': [5, 4, 0, 0, 3], 'Book2': [4, 0, 5, 4, 2], 'Book3': [0, 2, 4, 5, 0], 'Book4': [3, 4, 0, 0, 5], 'Book5': [0, 0, 3, 4, 4] }

df = pd.DataFrame(data)

def get_recommendations(user, df): user_ratings = df[df['User'] == user].iloc[:, 1:] similar_users = df[df['User'] != user].iloc[:, 1:]

similarities = cosine_similarity(user_ratings, similar_users)[0]

similar_user_index = similarities.argmax()

recommendations = similar_users.iloc[similar_user_index]
recommended_books = recommendations[recommendations.apply(lambda x: x > 0)].index.tolist()

return recommended_books

user_recommendations = get_recommendations('User1', df) print(f"Recommended books for User1: {user_recommendations}")