https://github.com/muammar/ml4chem
ML4Chem: Machine Learning for Chemistry and Materials
Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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✓DOI references
Found 1 DOI reference(s) in README -
○Academic publication links
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○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (16.8%) to scientific vocabulary
Keywords
Repository
ML4Chem: Machine Learning for Chemistry and Materials
Basic Info
- Host: GitHub
- Owner: muammar
- License: other
- Language: Python
- Default Branch: master
- Homepage: https://ml4chem.dev
- Size: 2.78 MB
Statistics
- Stars: 98
- Watchers: 4
- Forks: 15
- Open Issues: 8
- Releases: 9
Topics
Metadata Files
README.md
About
ML4Chem is a package to deploy machine learning for chemistry and materials science. It is written in Python 3, and intends to offer modern and rich features to perform machine learning (ML) workflows for chemical physics.
A list of features and ML algorithms are shown below.
- PyTorch backend.
- 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!
- Documentation (work in progress).
- Explicit and idiomatic:
ml4chem.get_me_a_coffee(). - Distributed training in a data parallel paradigm aka mini-batches.
- Scalability and distributed computations are powered by Dask.
- Real-time tools to track status of your computations.
- Easy scaling up/down.
- Easy access to intermediate quantities:
NeuralNetwork.get_activations(X, numpy=True)orVAE.get_latent_space(X). - Messagepack serialization.
Notes
This package is under heavy development and might break at some points until it gets stabilized. It is in its infancy, so if you find there is an error, you might want to report it so that it can be improved. We also welcome pull requests if you find any part of ML4Chem should be improved. That would be very nice.
Citing
If you find this software useful, please use this bibtex to cite it:
@article{El_Khatib2020,
author = "Muammar El Khatib and Wibe de Jong",
title = "{ML4Chem: A Machine Learning Package for Chemistry and Materials Science}",
year = "2020",
month = "3",
url = "https://chemrxiv.org/articles/ML4Chem_A_Machine_Learning_Package_for_Chemistry_and_Materials_Science/11952516",
doi = "10.26434/chemrxiv.11952516.v1"
}
Documentation
To get started, read the documentation at https://ml4chem.dev. It is arranged in a way that you can go through the theory as well as some code snippets to understand how to use this software. Additionally, you can dive through the module index to get more information about different classes and functions of ML4Chem. If you think the documentation has to be improved do not hesistate to state so in the bug reports and help out if you feel like it.
Visualizations
Copyright
License: BSD 3-clause "New" or "Revised" License.
``` ML4Chem: Machine Learning for Chemistry and Materials (ML4Chem) Copyright (c) 2019, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.
If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Intellectual Property Office at IPO@lbl.gov.
NOTICE. This Software was developed under funding from the U.S. Department of Energy and the U.S. Government consequently retains certain rights. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, distribute copies to the public, prepare derivative works, and perform publicly and display publicly, and to permit other to do so. ```
Owner
- Name: Muammar El Khatib
- Login: muammar
- Kind: user
- Location: Boston, Massachusetts
- Company: Bristol-Myers-Squibb
- Website: https://muammar.me
- Repositories: 16
- Profile: https://github.com/muammar
I am a PhD in Theoretical Chemical Physics who also likes coding.
GitHub Events
Total
- Watch event: 3
- Push event: 1
Last Year
- Watch event: 3
- Push event: 1
Committers
Last synced: 8 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Muammar El Khatib | m****b@g****m | 392 |
| Jacklyn Gee | j****4@g****m | 7 |
| vishankkumar | v****r@a****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 13
- Total pull requests: 9
- Average time to close issues: about 1 month
- Average time to close pull requests: 3 days
- Total issue authors: 1
- Total pull request authors: 4
- Average comments per issue: 0.92
- Average comments per pull request: 0.44
- Merged pull requests: 6
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- muammar (13)
Pull Request Authors
- jacklyngee (3)
- muammar (3)
- eligardella (2)
- vishankkumar (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 48 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 10
- Total maintainers: 1
pypi.org: ml4chem
Machine learning for chemistry and materials.
- Homepage: https://github.com/muammar/ml4chem
- Documentation: https://ml4chem.readthedocs.io/
- License: other
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Latest release: 0.0.9
published almost 6 years ago
Rankings
Maintainers (1)
Dependencies
- ase *
- dask_ml *
- dscribe *
- joblib *
- matplotlib *
- msgpack_numpy *
- msgpack_python *
- numpy *
- pandas *
- pip *
- plotly *
- pytest *
- scikit_learn *
- scipy *
- seaborn *
- sphinx *
- sphinx_rtd_theme *
- ase *
- dask_ml *
- dscribe *
- joblib *
- matplotlib *
- msgpack >=0.6.0
- msgpack_numpy *
- msgpack_python *
- numpy *
- pandas *
- pip *
- plotly *
- pytest *
- scikit_learn *
- scipy *
- seaborn *
- torch *
- python 3.7