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Data science for Materials Science & Engineering
Materials Descriptors FACE CAMERA
for Data Science
In this module
• Enhance data using descriptors (this lecture)
• Analyze descriptors, calculate and visualize correlations (this lecture)
• Hands on tutorial using nanoHUB: modeling melting temperatures
• Homework assignment
Juan C. Verduzco, Zachary D. McClure, and Alejandro Strachan
jverduzc@purdue.edu|| zmcclure@purdue.edu|| strachan@purdue.edu
School of Materials Engineering & Network for Computational Nanotechnology
Purdue University
West Lafayette, Indiana USA
Materials Descriptors for data science - Hands-on tutorial 1
Learning objectives and prerequisites
FACE CAMERA
After completing this lecture you will:
• Enhance materials data using descriptors
• Periodic table data
• Surrogate properties and physics-based models
• Analyze descriptors, calculate correlations to rank descriptors
Pre-requisites:
• Basic programming skills
Materials Descriptors for data science - Hands-on tutorial 2
Use of descriptors vs. deep learning
Descriptors Machine
learning
Raw Deep Learning Output
data
Adapted from: Jha et al. Scientific reports. 2018 Dec 4;8(1):1-3.
Materials Descriptors for data science - Hands-on tutorial 3
Launch featureselect tool in nanoHUB
Launch first notebook
Materials Descriptors for data science - Hands-on tutorial 4
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