Dear Colleagues, 

nanoHUB (https://nanohub.org) and Citrine Informatics (https://citrine.io) are happy to announce an upcoming hands-on workshop on machine learning tools for physical  
sciences and engineering. This free and open workshop will focus on deep learning methods for material science including convolutional neural networks and autoencoders. 

Title: Deep learning methods for material science
Date/Time: 21st October 2020 / 1 PM – 2 PM EDT 

Registration is now open: https://nanohub.org/groups/ml/handsontraining

This workshop is a part of nanoHUB's Hands-on Data Science and Machine Learning Training Series and is aimed at active researchers and educators, no prior coding  
experience is required. In addition, all exercises will use nanoHUB cloud computing resources, no need to download or install any software. All you need is an internet  
connection and a browser. After the training sessions, you will be able to continue using nanoHUB for your research or class. We will also allot some time for Q/A, aiming  
to provide one-on-one guidance to solve your specific problems. 

You will find additional information and recorded material from our previous workshops at the series webpage: https://nanohub.org/groups/ml/handsontraining.  
This includes an introduction to Jupyter notebooks, querying databases, and training basic machine learning models such as neural networks for classification and regression.  

We hope that you can attend this workshop and walk away with enough information and practical skills to kickstart your foray into deep learning methods for your research or classroom use.

You can find past Citrine informatics workshops at https://citrine.io/success/webinars/.

Prof. Ale Strachan, Materials Engineering, Purdue University
Deputy Director, nanoHUB. http://nanohub.org/

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Alejandro Strachan

Professor of Materials Engineering, Purdue University

Network for Computational Nanotechnology - nanohub.org

Center for Predictive Materials and Devices (c-PRIMED)