Project Title: Yelp-Like Recommendation System(recsys)

Project Description

Developed a Yelp-Like recommendation system using Yelp API data that utilizes two basic algorithms, Collaborative Filtering and Content-Based Filtering.

The application is built as a full-stack web application using Python3 and Django as the backend, and HTML5, CSS, and Bootstrap as the frontend.

The project provides personalized recommendations to users based on their cities, improving the user experience and increasing engagement with the Yelp platform.

The application is deployed on AWS using ngnix, and the project includes unit tests for the full application.

To view the project online, click here, you will redirect to the home page of this project.

Responsibilities:

• Utilized Yelp API to fetch user data, restaurant data, and reviews
• Implemented Collaborative Filtering and Content-Based Filtering algorithms to generate recommendations
• Built a full-stack web application using Python3, Django, HTML5, CSS, and Bootstrap
• Designed and implemented the user interface and user experience
• Implemented unit tests for the full application
• Deployed the application on an AWS EC2 instance using ngnix for public access

Key Technologies

Key Technologies: Python3, Django, HTML5, CSS, Bootstrap, Yelp API, AWS, ngnix, Unit Testing

Login Page

Business_index Page

This page serves as the home page of the recsys.

Install Requirements

asgiref==3.6.0
charset-normalizer==3.1.0
Django==4.1
django-bootstrap5==22.2
idna==3.4
mysqlclient==2.1.1
pytz==2022.7.1
requests==2.28.2
sqlparse==0.4.3
typing_extensions==4.5.0
tzdata==2023.2
urllib3==1.26.15
wincertstore==0.2