Machine learning for chemistry
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:
- 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.
Note: This package is under development.
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