This machine learning project aims to predict restaurant ratings, build recommender system as well as gather some insights about restaurants.

This data science project aims to gather insights into various factors affecting restaurants

This project predicts restaurant ratings based on various factors such as online orders, table bookings, restaurant type, location, and cuisine. Machine learning models were trained and deployed using Flask to provide real-time predictions.

This project focuses on building a restaurant rating prediction model using machine learning techniques. The model aims to predict ratings of restaurant based on various demographic and restaurant-customer-related features

This data science project aims to gather insights into various factors affecting restaurants

LounasFinder: An interactive web application for discovering and reviewing the best lunch spots. Leveraging Google Maps API and Firebase, it offers a user-friendly platform for finding the perfect meal based on location, cuisine, and user ratings.

This machine learning project aims to predict restaurant ratings, build recommender system as well as gather some insights about restaurants.