Movie Recommendation System using SBERT & Browsing History

A machine learning-powered movie recommendation system that analyzes a user’s browsing history to suggest movies they might like. It uses Sentence-BERT (SBERT) embeddings to compute similarities between movie descriptions and the user's past online activity.

Tech Stack

• Python (Core language)
• Flask (API for interacting with the system)
• Sentence-BERT (SBERT) (Text embeddings for similarity comparisons)
• PyTorch (For efficient tensor computations)
• Pandas (For history preprocessing)