Metadata-Version: 2.1
Name: shadow-ssml
Version: 1.0.0
Summary: Semi-supervised machine learning for PyTorch.
Home-page: https://github.com/sandialabs/shadow
Author: Shadow Developers
Author-email: dzander@sandia.gov
Maintainer-email: dzander@sandia.gov
License: Revised BSD
Description: ![Shadow](doc/source/figures/logo.png)
        ======================================
        
        [![Build Status](https://travis-ci.org/sandialabs/shadow.svg?branch=master)](https://travis-ci.org/sandialabs/shadow)
        [![Coverage Status](https://coveralls.io/repos/github/sandialabs/shadow/badge.svg?branch=master)](https://coveralls.io/github/sandialabs/shadow?branch=master)
        [![Documentation Status](https://readthedocs.org/projects/shadow-ssml/badge/?version=latest)](https://shadow-ssml.readthedocs.io/en/latest/?badge=latest)
        [![Downloads](https://pepy.tech/badge/shadow-ssml)](https://pepy.tech/project/shadow-ssml)
        
        Shadow is a [PyTorch](https://pytorch.org/) based library for semi-supervised machine learning.
        The `shadow` python 3 package includes implementations of Virtual Adversarial Training,
        Mean Teacher, and Exponential Averaging Adversarial Training.
        Semi-supervised learning enables training a model (gold dashed line) from both labeled (red and
        blue) and unlabeled (grey) data, and is typically used in contexts in which labels are expensive
        to obtain but unlabeled examples are plentiful.
        
        ![SSML for half moons](doc/source/figures/ssml-halfmoons.png)
        
        For more information, go to https://shadow-ssml.readthedocs.io/en/latest/
        
        Installation
        ------------
        Shadow can by installed directly from pypi as:
        ```
        pip install shadow-ssml
        ```
        
        Citing Shadow
        --------------
        * Linville, Lisa, et al. "Semi-supervised learning for seismic monitoring applications". In preparation. (2020).
        
        License
        -------
        Revised BSD. See the LICENSE.txt file.
        
        Contact
        -------
        * Dylan Anderson, Sandia National Laboratories, dzander@sandia.gov
        * Lisa Linville, Sandia National Laboratories, llinvil@sandia.gov
        
        Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
        
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
