[Bnc-faculty-all-list] FW: Hands-on training on data science & machine learning @ nanoHUB - Sign up for free today, Please Forward

Turner, Jaime J jjbiggs at purdue.edu
Fri Apr 3 16:31:25 EDT 2020


Forwarded on behalf of Prof. Alejandro Strachan, Materials Engineering, Deputy Director, nanoHUB

________________________________


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/
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