Foodr

Foodr recommends food places for users either through one of our 3 quick search buttons, or through a machine learning algorithm that recommends you food based on your mood, time of day, and other factors. Every time one "thumbs up" a restaurant to learn more about it, a decision tree classifier makes a better prediction for a restaurant the user may like.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

What things you need to install the software

-- Python3
-- Flask
-- SKLearn

Installing

A step by step series of examples that tell you how to get a development env running

1. Install Sklearn

pip install -U scikit-learn

2. Install flask

pip install flask

3. Once installed, open up flask_app.py in your favorite ide and run it. If you want to use terminal, set directory to 'HACKUCI2019/' and use command:

python flask_app.py

Built With

• MaterializeCSS - The html framework used
• Flask - web framework

Authors

• Michael Kirk - API integration
• Francisco Loya - Machine Learning/UX
• Animesh Agrawal - Back end

License

This project is licensed under the MIT License

Acknowledgments

• MaterializeCSS team
• Unsplash artists
  • White and blue brick photo by Patrick Tomasso on Unsplash
  • Pocket watch photo by Veri Ivanova on Unsplash
  • Food photo by Rachel Park on Unsplash