This is the Nipype Tutorial in Notebooks. There are multiple ways of how you can profit from this tutorial:
- Nipype Tutorial Homepage: You can find all notebooks used in this tutorial on this homepage.
- Nipype Tutorial Docker Image: Run the notebooks of this tutorial in an interactive docker image and on real example data. The nipype tutorial docker image is the best interactive way to learn Nipype.
If you want to help with this tutorial or have any questions, fell free to fork the repo of the Notebooks or interact with other contributors on the slack channel brainhack.slack.com/messages/nipype/. If you have any questions or found a problem, open a new issue on github.
A huge thanks to Michael Waskom, Oscar Esteban, Chris Gorgolewski and Satrajit Ghosh for their input to this tutorial! And a huge thanks to Dorota Jarecka who updated this tutorial to Python 3 and is helping me with keeping this tutorial updated and running!