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Introduction to Machine Learning in MSE: Predicting Bulk Modulus
In this module, you will learn how to predict bulk modulus using machine learning.
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Abstract
In this tool, you will learn how to...
- Predict bulk modulus using machine learning
- Use data based algorithms to sort large and complex data
- Apply clustering, classification and regression to data in a Materials Engineering context
- Make predictions and identify trends
Matminer is a materials focused machine learning program. The program can help with...
- Retrieving data from many different data bases
- Featurizing the data so that the data are usable for machine learning
- Creating interactive visualizations
Bio
Link to Dr. Peilin Liao's faculty page
https://engineering.purdue.edu/MSE/people/ptProfile?resource_id=143902&group_id=11984
Link to Adrian Nat Gentry's Linkedin page
https://www.linkedin.com/in/adrian-nat-gentry/
Cite this work
Researchers should cite this work as follows:
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This notebook is adapted from "Matminer introduction - Predicting bulk modulus"
https://github.com/hackingmaterials/matminer_examples/blob/master/matminer_examples/machine_learning-nb/bulk_modulus.ipynb
Ward, L., Dunn, A., Faghaninia, A., Zimmermann, N. E. R., Bajaj, S., Wang, Q.,
Montoya, J. H., Chen, J., Bystrom, K., Dylla, M., Chard, K., Asta, M., Persson,
K., Snyder, G. J., Foster, I., Jain, A., Matminer: An open source toolkit for
materials data mining. Comput. Mater. Sci. 152, 60-69 (2018).