Software Dependencies

The course, slides and exercises are primarily done using Python 3.6 and Jupyter Notebook 5.5. The binder/repo2docker-compatible environment](https://github.com/jupyter/repo2docker) can be found at binder/environment.yml. A full copy of the environment at the time the class was given is available in the wiki file. As many of these packages are frequently updated we have also made a copy of the docker image produced by repo2docker uploaded to Docker Hub at https://hub.docker.com/r/kmader/qbi2018/

All Lectures

The packages which are required for all lectures

• numpy
• matplotlib
• scipy
• scikit-image
• scikit-learn
• ipyvolume

Machine Learning Packages

For machine learning and big data lectures a few additional packages are required

• tensorflow
• pytorch
• opencv
• dask
• dask_ndmeasure
• dask_ndmorph
• dask_ndfilter

Image Registration / Medical Image Data

For the image registration lecture and medical image data

• itk
• SimpleITK
• itkwidgets