Movie2Vec: Neural Movie Recommendations

Adapting word embedding techniques for personalized movie suggestions

Developed an innovative movie recommendation system by adapting the Word2Vec neural network architecture, traditionally used for natural language processing, to understand and predict movie preferences based on user viewing patterns.

Leveraging the extensive MovieLens dataset, the system learns to represent movies in a multi-dimensional space where similar movies cluster together, enabling intuitive and accurate recommendations based on viewing history.