Smart Swiggy Recommendation System ML with Streamlit
This project develops a smart food recommendation system using machine learning and Streamlit to provide personalized restaurant and cuisine suggestions. It analyzes user preferences, order history, and behavioral patterns using techniques like PCA and K-Means clustering. The system delivers real-time, customized recommendations through an interactive web interface, enhancing user experience in food delivery platforms.
Project ID: 0685
Sub domains: Machine Learning, Recommendation Systems, Data Science, Web Development
Domain: Python
Project Year: 2026
Keywords: Recommendation System Machine Learning K-Means Clustering PCA Streamlit Data Analysis Personalized Suggestions Food Delivery
Project Cost : ₹6500
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