Skip to main content

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.

Examples

  • Tutorial 1: Assess and fit a single model from all data: Open In Colab
  • Tutorial 2: Use model hosted on Docker Hub: Open In Colab

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

Acknowledgments

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

madml-2.6.7.tar.gz (18.8 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

madml-2.6.7-py3-none-any.whl (18.8 MB view details)

Uploaded Python 3

File details

Details for the file madml-2.6.7.tar.gz.

File metadata

  • Download URL: madml-2.6.7.tar.gz
  • Upload date:
  • Size: 18.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for madml-2.6.7.tar.gz
Algorithm Hash digest
SHA256 2771a592641ed579a525e4c0e71877b56b68947ad1eb8210c59f694364a9aaff
MD5 e3dc81f8649c0123b58cc5049164ffe8
BLAKE2b-256 abd381281a7d1a823bfdf44254010b9ae45f802ef57acac0b830a6d336a6e9e5

See more details on using hashes here.

File details

Details for the file madml-2.6.7-py3-none-any.whl.

File metadata

  • Download URL: madml-2.6.7-py3-none-any.whl
  • Upload date:
  • Size: 18.8 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for madml-2.6.7-py3-none-any.whl
Algorithm Hash digest
SHA256 fde9eacce6cd974033744898b4c56c0f9dea042cc91958ed422b8cf4bb73efdd
MD5 7bdb551b1024fc27ab4959ffdeab62ce
BLAKE2b-256 edb341c53d41bdb67597a622e1971ba896ebcb513117b283ee5d71a212a3beea

See more details on using hashes here.

Release history Release notifications | RSS feed

This release

2.6.7 This release

2 files

2.6.6

2 files

2.6.5

2 files

2.6.4

2 files

2.6.3

2 files

2.6.2

2 files

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page