The beerbrain project aims to classify beer recipy by style with the help of a neural network using the aptly named brain Javascript library. The goal is to train a neural network to recognise the beer style of a beer recipe simply by looking at the recipe's properties, such as alcohol level, color, bitterness, ingredients, etc.

beerbrain is a simple Coffee-Script project that runs on node. To get up and running you simply need to clone the project:

git clone [email protected]:Microbrewit/beerbrain.git cd beerbrain 

Install coffee-script (if not already installed) and npm modules:

npm install coffee-script -g npm install 

Note! You will need at least Node.js version ~0.12 and CoffeeScript >= 1.9. Node.js >=4.0.0 supports a lot of EcmaScript6 features out of the box. In such a case you might not need to specify the --harmony option whe running the beerbrain application.

cp config/config.coffee.example config/config.coffee open config/config.coffee 

The first object in the config.coffee file is related to the neural network and the default values can be used. Feel free to experiment with the values though as you might be able to squeeze out better results and/or performance.

The following object specifies properties to use for the Microbrew.it api and currently includes only the api URL.

exports.microbrewit = apiUrl: 'http://brewsite.example' 

Running the application is super simple. It accepts one argument which is the task to run, e.g. coffee --nodejs --harmony index.coffee train|classify. The --nodejs --harmony options tells the coffee command to pass the --harmony option to node. The --harmony option enables Node.js' EcmaScript6 features such as Generators.

If you run Node.js >= 4.0.0 you are good to go and can likely omit the flags.

# Train the data coffee --nodejs --harmony index.coffee train # Classify the data coffee --nodejs --harmony index.coffee classify