.venv/scripts/activate python manage.py runserver

Developed a Book Recommendation System using the GoodBooks-10k dataset, leveraging machine learning techniques such as FunkSVD and Term Frequency to provide personalized book suggestions based on user ratings. The system preprocesses data to clean missing values and duplicates, while also using collaborative filtering and content-based methods to recommend books by similar authors or genres. Key features include dynamic book suggestions, user-friendly interface with AJAX integration, and scalable backend built with Django. Future improvements involve adding popular books, model optimization, and advanced recommendation algorithms.