Movie Recommendations Model

This model provides movie recommendations based on collaborative filtering (SVD).

Model Description

This model is based on Singular Value Decomposition (SVD), a matrix factorization technique commonly used for building recommendation systems. It predicts the preferences of users for movies based on historical ratings data.

How to Use

To use this model, you can load it and make predictions using the following Python code:

import pickle

# Load the model
with open("svd_model.pkl", "rb") as f:
    model = pickle.load(f)

# Get movie recommendations for a specific user
user_id = 123
recommendations = model.get_recommendations(user_id)

print("Recommended movies:", recommendations)