Metadata-Version: 2.1
Name: madml
Version: 2.6.7
Summary: Application domain of machine learning in materials science.
Home-page: https://github.com/leschultz/materials_application_domain_machine_learning.git
Author: Lane E. Schultz
Author-email: laneenriqueschultz@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: matplotlib
Requires-Dist: scipy
Requires-Dist: scikit-learn
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: pathos
Requires-Dist: tqdm
Requires-Dist: pytest
Requires-Dist: openpyxl
Requires-Dist: docker
Requires-Dist: tensorflow
Requires-Dist: udocker
Requires-Dist: scikeras
Requires-Dist: shap
Requires-Dist: kneed

# Materials Application Domain Machine Learning (MADML)

Research with respect to application domain with a materials science emphasis is contained within. The GitHub repo can be found in [here](https://github.com/leschultz/application_domain.git).

## Examples

* Tutorial 1: Assess and fit a single model from all data: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/leschultz/materials_application_domain_machine_learning/blob/main/examples/jupyter/tutorial_1.ipynb)
* Tutorial 2: Use model hosted on Docker Hub: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/leschultz/materials_application_domain_machine_learning/blob/main/examples/jupyter/tutorial_2.ipynb)

## Structure
The structure of the code packages is as follows:

```
materials_application_domain_machine_learning/
├── examples
│   ├── jupyter
│   └── single_runs
├── src
│   └── madml
└── tests
```

## Coding Style

Python scripts follow PEP 8 guidelines. A usefull tool to use to check a coding style is pycodestyle.

```
pycodestyle <script>
```

## Authors

### Graduate Students
* **Lane Schultz** - *Main Contributer* - [leschultz](https://github.com/leschultz)

## Acknowledgments

* The [Computational Materials Group (CMG)](https://matmodel.engr.wisc.edu/) at the University of Wisconsin - Madison
* Professor Dane Morgan [ddmorgan](https://github.com/ddmorgan) and Dr. Ryan Jacobs [rjacobs914](https://github.com/rjacobs914) for computational material science guidence
