The objective of this project is to develop a recommendation system that suggests products to users based on browsing history and preferences using machine learning techniques, improving personalization and customer engagement.
Collect e-commerce product and user interaction data Preprocess user behavior datasets Implement collaborative and content-based filtering Train recommendation models Evaluate recommendation accuracy Develop user login and product browsing interface Display personalized recommendations Implement feedback mechanism Optimize system performance Conduct testing and analysis Prepare project documentation
