Developed a Deep Learning and Artificial Neural Network based Hybrid Recommendation Model that blends deep neural network based collaborative filtering and content-based models to overcome the limitations of individual models and give more relevant and personalized recommendations.
It leverages the power of Google’s BERT language transformer for text vectorization and addresses the challenge of recommending from a large catalog of items using the "Candidate Generation, Retrieval, and Ranking Process".
