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<!DOCTYPE html>
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<title>ORMIR - Questions?</title>
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<li class="dropdown"><a href="#"><span>About us</span> <i class="bi bi-chevron-down"></i></a>
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<h2>I WANT TO JOIN!</h2>
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We are extremely excited that you want to join us!
<br>
In this page, find <a href="#cta-link">how to join us</a>
and how to <a href="#learning-os">learn more about Open Science</a>
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<h3>How to join the ORMIR community</h3>
<p> Write us! We will answer all your questions about the ORMIR community
<br>
and support you in finding your way to contribute! </p>
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<h4><span>Learning more about Open Science</span></h4>
<br>
Start warming up about Open Science! If you want to know more about Open Science and the Jupyter/Python environment, here is a collection of ebooks, tutorials, examples of Jupyter notebooks, and cheat sheets. All free and open!
</div>
<!-- <h5>Tutorials</h5> -->
<h5>Free eBooks</h5>
<ul class="custom-list-tight">
<li>
<a href="https://nasa.github.io/Transform-to-Open-Science-Book/index.html">Transform to Open Science</a>: NASA's book on how to do Open Science
</li>
<li>
<a href="https://the-turing-way.netlify.app/index.html">The Turing Way</a>: Book on how to do Open Science created by the Turing Way Community
</li>
<li>
<a href="https://learn.scientific-python.org/development/">Scientific Python Library Development Guide</a>: Guide to proper Python packaging, testing, etc.
</li>
</ul>
<h5>Video tutorials</h5>
<ul class="custom-list-tight">
<li>
<a href="https://www.youtube.com/playlist?list=PLj8QFvBykB7cdVPr6CY08UyPPPzy8R2Ar">Transparent Research 101</a>: Overview playlist on why and how to do open and reproducible research
</li>
<li>
<a href="https://www.youtube.com/playlist?list=PLj8QFvBykB7fGEH274TlqhToqGd_Qxt1H">Jupyter notebook and python for scientists</a>: Overview of the Jupyter/python environment
</li>
<li>
<a href="https://www.youtube.com/user/EnthoughtMedia/videos">Scipy conference</a>: In between conference talks, there are tutorials on Jupyter and the main scientific libraries
</li>
<li>
<a href="https://www.youtube.com/user/PyDataTV">pyData conference</a>: In between conference talks, there are tutorials on Jupyter and the main scientific libraries
</li>
</ul>
<h5>Hands-on tutorials</h5>
<ul class="custom-list-tight">
<li>
<a href="http://insightsoftwareconsortium.github.io/SimpleITK-Notebooks/">SimpleITK notebooks</a>: Collection of all the SimpleITK functionalities: image I/O, filters, etc.
</li>
<li>
<a href="https://simpleitk.org/SPIE2019_COURSE/">SPIE 2019 workshop</a>: Tutorial on how to use SimpleITK
</li>
<li>
<a href="https://github.com/sbonaretti/2020_OpenMR_jupyter">OpenMR Benelux 2020</a>: Basic Python and one medical image analysis example
</li>
<li>
<a href="https://github.com/ozan-oktay/Medical-Image-Analysis-IPython-Tutorials">Imperial College</a>: Notebooks for an academic course
</li>
</ul>
<h5>Examples of notebooks in medical image analysis</h5>
<ul class="custom-list-tight">
<li>
<a href="nb_gallery.html">ORMIR community notebooks</a>: Notebooks created by our community!
</li>
<li>
<a href="https://github.com/JCMSK/nb_gallery">JCMSK notebooks</a>: Our notebooks on musculosketelal imaging-based research
</li>
<li>
<a href="https://miykael.github.io/nipype_tutorial/">Nipype</a>: Several notebook tutorials on how to use Nipype (neuroimaging)
</li>
<li>
<a href="https://github.com/DLTK/DLTK/tree/master/examples/tutorials">DLTK</a>: Examples for a deep learning package
</li>
</ul>
<h5>Examples of notebooks in other fields</h5>
<ul class="custom-list-tight">
<li>
<a href="https://github.com/jupyter/jupyter/wiki#a-gallery-of-interesting-jupyter-notebooks">A gallery of interesting Jupyter Notebooks</a>: Notebooks used in other disciplines and for various purposes
</li>
</ul>
<h5>Cheat sheets</h5>
<!-- <p>
There are plenty of cheat sheets online that summarize main commands and tricks for python and its packages. Here the links to some of them:
</p> -->
<ul class="custom-list-tight">
<li>
Python:
<a href="https://ehmatthes.github.io/pcc/cheatsheets/README.html">example1</a>,
<a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf">example2</a>,
<a href="https://s3.amazonaws.com/dq-blog-files/python-cheat-sheet-basic.pdf">example3</a>
</li>
<li>
NumPy (linear algebra):
<a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Numpy_Python_Cheat_Sheet.pdf">example1</a>,
<a href="https://s3.amazonaws.com/dq-blog-files/numpy-cheat-sheet.pdf">example2</a>
</li>
<li>
Matplotlib (visualization):
<a href="https://github.com/matplotlib/cheatsheets">example1</a>
</li>
<li>
Pandas (tabular data analysis):
<a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Pandas_Cheat_Sheet_2.pdf">example1</a>,
<a href="https://drive.google.com/file/d/1UHK8wtWbADvHKXFC937IS6MTnlSZC_zB/view">exemple2</a>
</li>
</ul>
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