Machine Learning Recommendation System

Developed a sophisticated hybrid recommendation system that combines collaborative filtering and content-based filtering techniques to deliver highly personalized product and content suggestions to users.

The system leverages advanced machine learning algorithms to analyze user behavior patterns, preferences, and item characteristics to generate accurate recommendations similar to those used by Netflix and Amazon.

Implemented comprehensive evaluation metrics including Mean Squared Error optimization and Precision/Recall tuning to ensure high-quality recommendations and enhanced user engagement.