This repo includes the whole code of a swiggy-clone which was made under the guidance of Akshay Saini's course Namaste React, right now it is in development you can check it out in the below deployed link

This repository contains Namaste React Learning and INT252 Classroom Learning codes

Tasty-Tornado is a web application that allows users to search for restaurants and browse through real-time restaurant information. With FoodSale, users can easily find and order food from a variety of restaurants with using Swiggy Live Api.

Just a UI clone of Swiggy Landing page

Swiggy Data Analysis Using Power BI

This repo includes the code of a food delivery application built using react.js, where user can order food from any restaurant to their home. You can check it out in the below deployed link

This project is focused on building the user interface for a food delivery website. It aims to provide a clean, responsive, and user-friendly design to enhance the overall food ordering experience.

the 'Swiggy Restaurant Recommendation Model,' simplifies decision-making by using data science and machine learning. It offers personalized restaurant suggestions to users based on their cuisine and location preferences. The process involves data scraping, cleaning, machine learning, and the creation of an interactive web app for an enhanced dining

Swiggy Clone - Food delivery built with react , redux , tailwind css. Uses swiggy live API data for fetching Restaurants and Menu in the Restaurants . Uses google maps API for fetching the locations. Uses github api for user data

In this project, we conducted an analysis of Bangalore restaurant cuisines using data collected from Swiggy, a popular food delivery platform. We utilized Python and MS Excel to gather, organize, and analyze the data.

Food ordering web application using react JS (Use Swiggy live API for data) & design UI using Tailwind CSS