Organizers.
Marjolein Dijkstra (University of Utrecht, m.dijkstra@uu.nl)
Andrew Ferguson (University of Chicago, andrewferguson@uchicago.edu)
Erik Luijten (Northwestern University, luijten@northwestern.edu)
Overview.
Data-driven modeling approaches and machine learning have opened new paradigms in the understanding, engineering, and design of colloidal suspensions, complex fluids, granular matter, and other soft matter systems. This workshop will bring together theoretical, computational, and experimental researchers from different scientific communities to advance interdisciplinary collaboration and understanding in data-enabled design of soft materials.
"Hands-On Machine Learning with Python" Workshop
3:30-6 pm, Tue 11 Dec
The “Hands-On Machine Learning with Python” workshop is open to all interested attendees. Participants will require their own laptop with a working Anaconda Python 2.7 installation equipped with all required libraries.

Coverage. Depending on time and interest, the workshop will cover Python fundamentals, principal components analysis (PCA), diffusion maps (dMaps), and artificial neural networks (ANN). Attendees will leave the workshop with an understanding of the theoretical underpinnings of the techniques, see the tools in practice through live examples, and take away with them a working Python implementation of the tool that can be adapted to their own applications.

Pre-Reqs. Prior to the workshop, attendees are requested to do the following:

1. Download the corse materials here (~56 MB download).

2. Follow the instructions in ./1_Anaconda_install/Anaconda_install.pdf to install a working Anaconda Python 2.7 release. This must be done in advance of the workshop as there will not be time or wireless bandwidth to do the installation live.

3. Attendees unfamiliar with Python are recommended to read ./2_Python_intro/Python_intro.pdf and work through the accompanying Jupyter Notebook ./2_Python_intro/Python_intro.ipynb to familiarize themselves with the fundamentals of the language.
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