Predictive Beer Analytics is a project that aims to gather, process, and present beer data in such a way that the user can find out based on the desired characteristics of the beer where in the world that
particular beer is enjoyed. Other fun tools for beer marketing is also included such as color and word rating analyser.

A live version of the web application can be found at http://jweinstein92.pythonanywhere.com/

Josh Weinstein Jim Sundkvist Marek Kühn

Within the project you'll find the following directories:

Predictive_Beer_Analytics/
├── app/
├── docs/
├── machine_learning/
│   ├── data/
│	├── graphics/
│   └── lib/
└── static/
    ├── css
    ├── images
    └── js

In the app directory you will find the project's Django project that is used as a GUI for the mined and processed data. In the docs directory you will find the projects documentation. In the machine_learning directory you will find the data mining and machine learning scripts as well as sample data. In the static directory you will find css, images, and javascript files that are used in the Django web application.

Predictive Beer Analytics documentation is included in the project, under the docs directory. Or can be accessed here

argparse>=1.2
jsonpickle>=0.8
nltk>=3.0
matplotlib>=1.4.2
numpy>=1.9.0
scikit-learn>=0.15.2
scipy>=0.14.0
sphinx>=1.2.3
django>=1.7.0
mysql>=5.6.22

See documentation

Josh Weinstein: joshweinstein92@gmail.com Marek Kühn: kuhnm@centrum.cz Jim Sundkvist: jimsudket@gmail.com

Thanks to Untappd.com for allowing us to mine the data necessary to bring this project about.