Recommendation systems have been an integral part of our digital lives, significantly influencing our daily decision-making process and serving as critical tools in numerous sectors, including but not limited to e-commerce, social media and entertainment.
This project, thus, aimed to design a recommendation system to make content discovery more straightforward.
The process includes building a model for the Netflix Prize Dataset using the Collaborative Filtering technique, specifically via SVD-Inspired algorithms (Matrix Factorization) using the scikit-surprise library and evaluating its performance via metrics like RMSE and MAE.
The results of this project are promising, with relatively good accuracy and demonstrate the potential of machine learning techniques in enhancing movie recommendations for users.