November 20, 2017 UMD Home FabLab AIMLab
MLMR 2017
Machine Learning
for
Materials Research
Bootcamp & Workshop
2017

Google Drive Documents

Instructions for preparing for the Boot Camp

As advertised, Python will be the language we will be using this year. Prior to coming to the Camp, please make sure that:

  1. Please have a laptop ready with Python Anaconda downloaded. The instruction on how to download it is on the website.
  2. If you are new to coding/Python, it would be good to go through some simple Python tutorials. Here is one for Anaconda
  3. We are having a poster session/dinner Thursday night. Please bring a poster on your favorite recent work!
  4. We are also still looking for some data to demonstrate the analysis techniques during the lectures. If you have some data you can share, please send them along.
  5. If you are driving to College Park every day, the visitor parking lot has changed on campus, and now you have to park in the Xfinity Center visitor lot. There is a map posted on the website. We are trying to get some free-parking codes. Send Martha Heil an email to let her know (mjheil@umd.edu) if you are planning to drive in every day. Please let us know if you have any questions.

We want to look at your data!

We would like to use some of your own data at the Camp for the actual exercises and demonstrations. If you have any data that you are cleared to share with the whole Camp group, please let us know. The types of data we are looking for are digitized image data, a large number (100-1000) of spectral/vector-like data, or any other types that you think might be of interest.

Remember the Poster Session Thursday night

We would like to have broad discussions on applications of machine learning to materials research at large. Please bring a poster from your research. It doesn't have to do with machine learning. We will discuss how machine learning can be applied.

Conference Support

Colleges A. James Clark School of Engineering
The College of Computer, Mathematical, and Natural Sciences

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