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Welcome to the Tutorial series for using the Materials Simulation Toolkit for Machine Learning (MAST-ML)!
MAST-ML is an open-source python package designed to broaden and accelerate the use of machine learning methods in materials science
Paper Citation: https://doi.org/10.1016/j.commatsci.2020.109544
Tutorial 1: Getting Started with MAST-ML
Tutorial 2: Data Import and Cleaning with MAST-ML
Tutorial 3: Feature Engineering with MAST-ML
Tutorial 4: Models and Data Splitting Tests with MAST-ML
Tutorial 5: Left out data, nested cross validation, and optimized models with MAST-ML
Tutorial 6: Model error analysis and uncertainty quantification with MAST-ML
University of Wisconsin-Madison Computational Materials Group
Jacobs, R., Mayeshiba, T., Afflerbach, B., Miles, L., Williams, M., Turner, M., Finkel, R., Morgan, D., "The Materials Simulation Toolkit for Machine Learning (MAST-ML): An automated open source toolkit to accelerate data-driven materials research", Computational Materials Science 175 (2020).
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