Hands-on training on data science & machine learning @ nanoHUB - Sign up for free today
Forwarding on behalf of Alejandro Strachan: Lisa Stacey Administrative Assistant to the Department Head School of Materials Engineering Neil Armstrong Hall of Engineering 701 West Stadium Ave West Lafayette, IN 47907 o: 765-494-4095 f: 765-494-1204 [3749DD84]<https://www.purdue.edu/?utm_source=signature&utm_medium=email&utm_campaign=purdue> ________________________________ Dear Colleagues, I hope you are all staying well during these unchartered times. Many of you may be experiencing restricted access to labs during the COVID-19 crisis. We at nanoHUB would like to offer our resources to help you stay productive and develop new skills, especially if you are looking to enhance your research with machine learning and data science. We have put together a series of open, hands-on tutorials and office hours that will jumpstart your use of data science and machine learning in research or teaching. Our series is aimed at active researchers and educators and 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. Importantly, we are allotting half the time in each session to Q/A, aiming to provide one-on-one guidance to solve your specific problems. The workshop is organized in 6 sessions, listed below. You can find more information and sign up links at https://nanohub.org/groups/ml/handsontraining Session 1: Intro to Jupyter in nanoHUB, Pandas for data organization and plotting Date/Time: Wednesday, 8th April 2020 / 11 AM – 12 PM EDT Session 2: Repositories and data management Date/Time: Friday, 10th April 2020 / 11 AM – 12 PM EDT Session 3: Supervised learning part 1: linear regression and neural networks Date/Time: Monday, 13th April 2020 / 11 AM – 12 PM EDT Session 4: Supervised learning part 2: classification and random forests Date/Time: Wednesday, 15th April 2020 / 11 AM – 12 PM EDT Session 5: Unsupervised learning: dimensionality reduction via matrix decomposition Date/Time: Friday, 17th April 2020 / 11 AM – 12 PM EDT Session 6: Sequential learning and design of experiments Date/Time: Monday, 20th April 2020 / 11 AM – 12 PM EDT We hope that you can attend this workshop and walk away with enough information and practical skills to kickstart your foray into machine learning methods for your research or classroom use. Best regards, Prof. Ale Strachan, Materials Engineering, Purdue University Deputy Director, nanoHUB. http://nanohub.org/
participants (1)
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Stacey, Lisa A