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Machine Learning in Materials Science: An Introduction through Python. Workshop as part of CNMS User Meeting 2019

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Machine Learning in Materials Science: An Introduction through Python

Workshop organized by R. Vasudevan and V. Sharma

This github repo was created as part of the above workshop, which is one of the workshops within the CNMS User Meeting 2019 held at Oak Ridge National Laboratory, August 12-14 2019.

Agenda

Time Details
8:00-9:00 AM Setup and installation
9:00-9:30 AM Introduction to machine learning in python
9:30-10:45 AM Basic signal and image processing
10:45-11:00AM Coffee Break
11:00-12:00 PM Talk - "Polymer Genome: An Informatics Platform for Polymer Design" (Huan Tran/GTech)
12:00-1:00 PM Lunch on your own
1:00-2:00 PM Classification and Regression Methods
2:00-3:00 PM Talk - "Applications of ML to Materials theory" (K. Choudhary/NIST)
3:00-3:15 PM Break
3:15-4:00 PM Spectral Unmixing Techniques
4:00-4:30 PM Deep Learning Methods: An overview

Most of the day will consist of working through Jupyter notebooks. These can either be run locally if you have the Jupyter notebook program and python installed (we reccomend Anaconda's distribution - https://www.anaconda.com/distribution/ ), or more easily these can be run online via google colab. Use the instructions below:

  1. Navigate to https://colab.research.google.com/
  2. Click on the Github tab. Allow authorization if prompted.
  3. Type https://github.com/pycroscopy/CNMS_ML_in_MS_Workshop_2019
  4. Select the notebook you wish to run

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