Forwarding on behalf of Prof. Ale Strachan, Materials Engineering, Purdue University Deputy Director, nanoHUB. http://nanohub.org/ : Thank you, Lisa Stacey Administrative Assistant to the Department Head School of Materials Engineering Neil Armstrong Hall of Engineering o: 765-494-4095 f: 765-494-1204 [3749DD84]<https://urldefense.proofpoint.com/v2/url?u=https-3A__www.purdue.edu_-3Futm-5Fsource-3Dsignature-26utm-5Fmedium-3Demail-26utm-5Fcampaign-3Dpurdue&d=DwMFAg&c=l45AxH-kUV29SRQusp9vYR0n1GycN4_2jInuKy6zbqQ&r=cYZgnbkB39R9SYPCvL_MkXuih1H-IjjKyRBtQtQ6ib8&m=H5ec4nXIY6Mt-FgrmXhcB1ClcZZRWvtSm3BzPca31UE&s=ra1N_tE4A3L7IxFqllrao41XR8k0ynZZYRxh3KMpTwY&e=> ________________________________ Subject: nanoHUB and Citrine Informatics free hands-on workshop on machine learning 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/<https://citrine.io/success/webinars/>. Prof. Ale Strachan, Materials Engineering, Purdue University Deputy Director, nanoHUB. http://nanohub.org/ -- Alejandro Strachan Professor of Materials Engineering, Purdue University Network for Computational Nanotechnology - nanohub.org<http://nanohub.org> Center for Predictive Materials and Devices (c-PRIMED)
