README

Welcome to MAML - Molecular Applied Machine Learning

This repository is a collection of tools which aim to improve the interface between computational chemistry and machine learning.

How do I get set up?

Setup is easy - above standard packages (numpy, scipy), we only have the dependency of Theano, which installs with pip

However, if you want to use the functional (multi-process) neural network code, you need to have python 2.7.8 or higher. We recommend doing this by installing anaconda http://docs.continuum.io/anaconda/install.html

Contribution guidelines

To contribute to this code, you should be prepared to be asked to provide some of the following:

• Writing tests

• Code review

• Documentation

Repository Tranisition

This repository is in transition from Bitbucket, and we are taking the opportunity to clean things up. New features are coming thick and fast!

Who do I talk to?

This repo is controlled by Ed Pyzer-Knapp, please email at epyzerknapp[at]fas.harvard.edu