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This set of tutorials and educational materials is being developed,IT IS NOT INTEGRATED IN THE HTML DOCS AThttps://www.numpy.org/devdocs/

The goal of this repository is to provide high-quality resources by theNumPy project, both for self-learning and for teaching classes with. If you'reinterested in adding your own content, check theContributingsection.

To download a local copy of the.ipynb files, you can eitherclone this repositoryor navigate to any of the documents listed below and download it individually.

0. Learn to write a NumPy tutorial: our style guide for writing tutorials.
1. Tutorial: Linear algebra on n-dimensional arrays
2. Tutorial: CS231n Python Tutorial
3. Tutorial: Determining Moore's Law with real data in NumPy
4. Tutorial: Saving and sharing your NumPy arrays
5. Tutorial: NumPy deep learning on MNIST from scratch

We very much welcome contributions! If you have an idea or proposal for a newtutorial, pleaseopen an issuewith an outline.

Don’t worry if English is not your first language, or if you can only come upwith a rough draft. Open source is a community effort. Do your best – we’ll helpfix issues.

Images and real-life data make text more engaging and powerful, but be sure whatyou use is appropriately licensed and available. Here again, even a rough ideafor artwork can be polished by others.

The choice of Jupyter Notebook in this repo instead of the usual format(reStructuredText, through Sphinx)used in the main NumPy documentation has two reasons:

• Jupyter notebooks are a common format for communicating scientificinformation.
• rST may present a barrier for some people who might otherwise be veryinterested in contributing tutorial material.

You may notice that some of our content is in markdown format (.md files).This is part of an ongoing restructuring of the repository workflow. However,you can still submit your content as a Jupyter Notebook file.

If you have your own tutorial in the form of a Jupyter notebook (a.ipynbfile) and you'd like to add it to the repository:

Go tohttps://github.com/numpy/numpy-tutorials/issuesand create a new issue with your proposal. Give as much detail as you can aboutwhat kind of content you would like to write (tutorial, how-to) and what youplan to cover. We will try to respond as quickly as possible with comments, ifapplicable.

You can use ourTutorial Style Guide to makeyour content consistent with our existing tutorials.

Remember to clear all outputs on your notebook before uploading it.

Fork this repository (if you haven't before).

In your own fork, create a new branch for your content.

Add your notebook to thecontent/ directory.


Update theenvironment.yml file with the dependencies for yourtutorial (only if you add new dependencies).

Update thisREADME.md to include your new entry.


Update the attribution section (below) to credit the original tutorialauthor, if applicable.

Create apull request.


🎉Wait for review!

For more information about GitHub and its workflow, you can seethis document.

• The cs231n tutorial is by@jcjohnson. The full tutorial inits original form is linked via [numpy.org][learn].
• The SVD tutorial is by@melissawm. The full tutorial is availablevia thetutorials page of the official NumPy documentation.

The following links may be useful:

• NumPy Code of Conduct
• Main NumPy documentation
• NumPy documentation team meeting notes
• NEP 44 - Restructuring the NumPy documentation
• Blog post - Documentation as a way to build Community

Note that regular documentation issues for NumPy can be found in themain NumPyrepository (see theDocumentationlabels there).