Chemical engineering ML
cheml is a toolkit for building, training, and deploying machine learning models tailored for chemical engineering applications. It provides utilities for data preprocessing, model selection, evaluation, and integration with chemical process data.
- Data loaders and preprocessors for chemical datasets
- Ready-to-use ML model templates (regression, classification)
- Model evaluation and visualization tools
- Support for scikit-learn, PyTorch, and TensorFlow
- Example workflows for common chemical engineering problems
git clone https://github.com/mv-per/cheml.git
cd chemlCheML uses conda for development. Please refer to conda documentation for conda installation. You can also use a conda alternative, such as the mamba package, that is a C++ implementation of conda.
With conda setup, you can generate the environment by
chmod +x ./scripts/create_dev_env.sh
./scripts/create_dev_env.shthen you can activate the environment by invoking:
conda activate cheml
The package uses pre-commit to lint and check typing on the files. Please initiate pre-commit on your machine by invoking:
pre-commit install
With the activated environment, one can build the package using the following command (that uses the invoke package):
inv build
- Predicting reaction yields
- Process optimization
- Property estimation
Contributions are welcome! Please open issues or submit pull requests.
MIT License