Improved implementation of NCF with added features for practical use

Welcome to the realm of the NCF Movie Recommender System, where the perfect movie match is just a recommendation away! 🚀

This journey through cinematic wonders and intelligent recommendations is powered by an ensemble of cutting-edge technologies:

What began as a humble desire to integrate Deep Learning into Collaborative Filtering evolved into an extraordinary tale of innovation:

1. Cold Start Conundrum Solved: We cast aside the shadows of the cold start problem by harnessing the power of Information Theory. New users are welcomed into a world of tailored recommendations.

2. Information Theory Magic: Information Theory becomes the spellbook, as we conjure unique user embeddings for new explorers. This masterstroke ignites a symphony of personalized recommendations.

3. Hyperparameters Perfected: Optuna, the hyperparameter oracle, guides the model's transformation. The art of hyperparameter tuning brings forth a model optimized for cinematic brilliance.

4. Empowering New Users: A twist in the plot – new users are invited to rate a curated film selection. This ritual empowers the model to unveil recommendations that captivate the heart and soul.

5. Evaluating Cinematic Excellence: Root Mean Squared Error (RMSE) takes the stage alongside the dynamic duo of Precision and Recall at K. Together, they redefine the metric of recommendation quality.

Join us on this cinematic odyssey by taking these steps:

1. There are no steps just run the notebook!!

The finale is yet to come! My ultimate vision is a Group Movie Recommender System – a single click to harmonize cinematic choices for our 6-person hostel room. Imagine the symphony of preferences as the model curates perfect movie nights.