* MAST-ML no longer uses an input file. The core functionality and workflow of MAST-ML has been rewritten to be more conducive to use in a Jupyter notebook environment. This major change has made the code more modular and transparent, and we believe more intuitive and easier to use in a research setting. The last version of MAST-ML to have input file support was version 2.0.20 on PyPi.
* Each component of MAST-ML can be run in a Jupyter notebook environment, either locally or through a cloud-based service like Google Colab. As a result, we have completely reworked our use-case tutorials and examples. All of these MAST-ML tutorials are in the form of Jupyter notebooks and can be found in the mastml/examples folder on Github.
* An active part of improving MAST-ML is to provide an automated, quantitative analysis of model domain assessement and model prediction uncertainty quantification (UQ). Version 3.x of MAST-ML includes more detailed implementation of model UQ using new and established techniques.