Main Objective:

The main agenda of this project is:

• Perform extensive Exploratory Data Analysis(EDA) on the Zomato Dataset.
• Build an appropriate Machine Learning Model that will help various Zomato Restaurants to predict their respective Ratings based on certain features.
• DEPLOY the Machine learning model via Flask that can be used to make live predictions of restaurant ratings.

Directory Structure:

Files you will need:

• Model.py file

• .csv file

• template

• .html file

• .css file

• app.y file

Model.py: This file contains the code for building our model that is used in predicting the restaurant ratings

CSV file: This contains our data that we have already cleaned and saved

template file: The template file contains the HTML and CSS documents used in building our web app

App.py: This contains the Flask APIs that receive restaurant details via GUI/API calls, then make the prediction of restaurant ratings based on our model and return the rate.