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.
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.
What things you need to install the software
-- Python3
-- Flask
-- SKLearn
A step by step series of examples that tell you how to get a development env running
- Install Sklearn
pip install -U scikit-learn
- Install flask
pip install flask
- 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
- MaterializeCSS - The html framework used
- Flask - web framework
- Michael Kirk - API integration
- Francisco Loya - Machine Learning/UX
- Animesh Agrawal - Back end
This project is licensed under the MIT License
- 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