Leveraging BERT for Tailored Movie Suggestions: A Machine Learning Approach

The Primary aim is to enhance the development of personalised movie suggestions by developing a content-based movie recommender system and offering consumers a well-chosen selection that aligns with their individual cinematic tastes. The study explores the complexities of content-based recommendation with the goal of revealing hidden patterns in the movie data and providing a more thorough, nuanced understanding of user preferences using efficient machine learning algorithms and NLP models such as BERT (Bidirectional Encoder Representations from Transformers)