Mobile phones, used by all ages, enhance convenience. Smartphones offer diverse functions Choosing the right one is tough due to myriad options. Users rely on reviews and prices for decisions.  Python web app aims to classify and rank smartphone features based on user preferences. It employs machine learning algorithms to analyze smartphone data and refine recommendations with user feedback. The user-friendly interface allows input of preferences for camera quality, battery life, display resolution, etc. By processing a dataset of smartphone features and user ratings,  apply regression analysis, clustering, and decision trees. It offers personalized smartphone recommendations, empowering users to make informed choices and enhance their smartphone experience.

• Machine Learning Recommendations
• Smartphone Selection
• User Preferences