nanoHUB and Citrine Informatics 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 materials 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:
There is a limit of 500 participants, so don’t delay. Even if you aren’t able to participate, the session will be recorded and made available shortly after the event takes place.
Once registered, you will receive an email 24 hours prior to the beginning of the session that contains a link to join.
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, with no need for you to download or install any software. All you’ll require 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:
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:
Prof. Ale Strachan, Materials Engineering, Purdue University
Deputy Director, nanoHUB.