This repository contains code for Recommendation of differents restaurants. Developed using Flask and python. Website is hosted on heroku.
It's live at https://restaurants-spotter.herokuapp.com/ .
The directory contains web sub directories and a sub directory for hosting model and other scripts:
-
app.py The file which contains all the main backend operations of the website and used to run the flask server locally.
-
Procfile for setting up heroku.
-
requirement.txt contains all the dependencies.
-
templates contains the html file.
|- - - home.html contains home page.
|- - - search.html contains search page.
-
static contains the css file and images.
|- - - home.css contains Styling of home page.
|- - - search.css contains Styling of Search page/ result page.
|- - - backgrund1.jpg contains background image of web pages.
-
main_rest.csv contains the raw data.
-
food1.csv contains cleaned data.
The entire code has been developed using Python programming language and is hosted on Heroku. The analysis and model is developed using ScikitLearn library. The website is developed using Flask.
- Open the
Terminal
. - Clone the repository by entering
$ git clone https://github.com/shsarv/Restaurant-Recommendation-System.git
. - Ensure that
Python3
andpip
are installed on the system. - change the diectory to repository name using
$ cd [Repository name]
. - Create a
virtualenv
by executing the following command:virtualenv env
. - Activate the
env
virtual environment by executing the follwing command:source env/bin/activate
. - Enter the cloned repository directory and execute
pip install -r requirements.txt
. - Now, execute the following command:
flask run
and it will point to thelocalhost
server with the port5000
. - Enter the
IP Address: http://localhost:5000
on a web browser and use the application.
The following dependencies can be found in requirements.txt:
- https://medium.com/the-andela-way/deploying-a-python-flask-app-to-heroku-41250bda27d0
- https://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.cosine_similarity.html
- https://www.machinelearningplus.com/nlp/cosine-similarity/
- https://towardsdatascience.com/cosine-similarity-how-does-it-measure-the-similarity-maths-behind-and-usage-in-python-50ad30aad7db
- https://uoa-eresearch.github.io/eresearch-cookbook/recipe/2014/11/26/python-virtual-env/
- Machine Learning course- https://www.coursera.org/learn/machine-learning/
- MIT License