Amp: Machine Learning for Atomistics v0.4

# Amp: Atomistic Machine-learning Potentials#

Developed by Andrew Peterson & Alireza Khorshidi, Brown University School of Engineering. *Amp* allows for the modular representation of the potential energy surface with descriptor and regression methods of choice for the user.

This project lives at:
https://bitbucket.org/andrewpeterson/amp

Documentation lives at:
http://amp.readthedocs.org

(This project was formerly known as "Neural". The last stable version of Neural can be found at https://bitbucket.org/andrewpeterson/neural)