Content-Based Recommendation System

Overview

Implemented a content-based filtering (CBF) recommendation system that embeds product description documents using BERT and recommends similar products based on dot-product similarity.

Key Achievements

• Built a product description document embedding pipeline using BERT models
• Implemented a similar product recommendation algorithm based on dot-product similarity

Tech Stack

• Model: BERT (HuggingFace Transformers)
• Framework: PyTorch