Metadata-Version: 2.1
Name: ml4chem
Version: 0.0.0
Summary: Machine learning for chemistry
Home-page: https://github.com/muammar/ml4chem
Author: Muammar El Khatib
Author-email: muammarelkhatib@gmail.com
License: UNKNOWN
Description: ML4Chem
        ===========
        
        ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/ml4chem.svg)
        [![Build Status](https://travis-ci.com/muammar/ml4chem.svg?branch=master)](https://travis-ci.com/muammar/ml4chem)
        
        
        **ML4Chem** is machine learning for chemistry.
        
        This package is written in Python 3, and intends to offer modern and rich
        features to perform machine learning workflows for chemical physics.
        
        A list of features and methods are shown below.
        
        - Atom-centered Neural Networks, and Kernel Ridge Regression for the prediction
          of total energies.
        - PyTorch backend.
        - GPU support.
        - ASE interface.
        - Completely modular. You can use any part of this package in your project.
        - Free software <3. No secrets! Pull requests and additions are more than
          welcome!
        - Good documentation (I hope!).
        - Explicit and idiomatic: `ml4chem.get_me_a_coffee()`.
        - Distributed training in a data parallelism paradigm (mini-batches).
        - Scalability and distributed computations are powered by Dask <3.
        - Real-time tools to track status of your computations.
        - [Messagepack serialization](https://msgpack.org/index.html).
        
        
        ## Dask dashboard
        ![](https://raw.githubusercontent.com/muammar/ml4chem/master/docs/source/_static/dask_dashboard.png)
        
        Note: This package is under development.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
