All Categories (1-4 of 4)

1. The Materials Simulation Toolkit for Machine Learning (MAST-ML): Automating Development and Evaluation of Machine Learning Models for Materials Property Prediction

   Online Presentations | 06 Oct 2022 | Contributor(s):: Ryan Jacobs

   Hands-on activities, we will use MAST-ML to (1) import materials datasets from online databases and clean and examine our input data, (2) conduct feature engineering analysis, including generation, preprocessing, and selection of features, (3) construct, evaluate and compare the performance of...

2. Sep 13 2022

   MAST-ML and Machine Learning Lab Module Workshop

   Join nanoHUB for a two-part set of  back-to-back ML workshops. Part I is an introduction to Machine Learning for Materials Science that is appropriate for people with no prior experience...

   https://nanohub.org/events/details/2229

3. The Materials Simulation Toolkit for Machine Learning (MAST-ML): Automating Development and Evaluation of Machine Learning Models for Materials Property Prediction

   Online Presentations | 25 Jun 2021 | Contributor(s):: Ryan Jacobs

   This tutorial contains an introduction to the use of the Materials Simulation Toolkit for Machine Learning (MAST-ML), a python package designed to broaden and accelerate the use of machine learning and data science methods for materials property prediction.

4. Materials Simulation Toolkit for Machine Learning (MAST-ML) tutorial

   Tools | 07 May 2021 | Contributor(s):: Ryan Jacobs, BENJAMIN AFFLERBACH

   Tutorial showing the many use cases for the MAST-ML package to build, evaluate and analyze machine learning models for materials applications.