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Göttingen DL course material

This is the repository for course material (input and output) for the "Mathematics of deep learning with an emphasis on inverse problems" course at Göttingen 2018.

Installing Dependencies

The latest version of ODL and some supporting libraries are needed in order to use these notebooks. See the installation instructions for further information.

Jupyter Notebooks

Part of the material will be published as Jupyter notebooks. If you're familiar with Mathematica notebooks, you won't be surprised.

To install the notebook software, you can either use conda:

conda install notebook

or pip:

pip install notebook

You can then start the software by running

jupyter notebook

in a terminal. Sometimes one gets OSError: [Errno 99] Cannot assign requested address. In this case an explicit IP has to be given, which should be the equivalent to localhost in your case:

jupyter notebook --ip=127.0.0.1

The notebooks can also be viewed online as static HTML pages. This works (somewhat) on GitHub directly, but better with nbviewer. Just copy the URL of the notebook into the text field at that page.

Feedback

If you find any errors or experience issues, please get back to us (@ozanoktem or @adler-j) or create an issue.

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Deep Learning course in Göttingen April 2018

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