diff --git a/content/en/learn.md b/content/en/learn.md index a56f90fa85..117cc0c731 100644 --- a/content/en/learn.md +++ b/content/en/learn.md @@ -7,30 +7,43 @@ For the **official NumPy documentation** visit [numpy.org/doc/stable](https://nu *** -Below is a curated collection of educational resources, both for self-learning and teaching others, developed by NumPy contributors and vetted by the community. +Below is a curated collection of educational resources, both for self-learning and +teaching others, developed by NumPy contributors and vetted by the community. ## Beginners -There's a ton of information about NumPy out there. If you are just starting, we'd strongly recommend the following: +There's a ton of information about NumPy out there. If you are just starting, we'd +strongly recommend the following: **Tutorials** * [NumPy Quickstart Tutorial](https://numpy.org/devdocs/user/quickstart.html) -* [NumPy Tutorials](https://numpy.org/numpy-tutorials) A collection of tutorials and educational materials in the format of Jupyter Notebooks developed and maintained by the NumPy Documentation team. To submit your own content, visit the [numpy-tutorials repository on GitHub](https://github.com/numpy/numpy-tutorials). -* [NumPy Illustrated: The Visual Guide to NumPy *by Lev Maximov*](https://betterprogramming.pub/3b1d4976de1d?sk=57b908a77aa44075a49293fa1631dd9b) -* [Scientific Python Lectures](https://lectures.scientific-python.org/) Besides covering NumPy, these lectures offer a broader introduction to the scientific Python ecosystem. +* [NumPy Tutorials](https://numpy.org/numpy-tutorials) A collection of tutorials and + educational materials in the format of Jupyter Notebooks developed and maintained by + the NumPy Documentation team. To submit your own content, visit the + [numpy-tutorials repository on GitHub](https://github.com/numpy/numpy-tutorials). +* [NumPy Illustrated: The Visual Guide to NumPy](https://betterprogramming.pub/3b1d4976de1d?sk=57b908a77aa44075a49293fa1631dd9b) + *by Lev Maximov* +* [Scientific Python Lectures](https://lectures.scientific-python.org/) Besides covering + NumPy, these lectures offer a broader introduction to the scientific Python ecosystem. * [NumPy: the absolute basics for beginners](https://numpy.org/devdocs/user/absolute_beginners.html) -* [NumPy tutorial *by Nicolas Rougier*](https://github.com/rougier/numpy-tutorial) -* [Stanford CS231 *by Justin Johnson*](http://cs231n.github.io/python-numpy-tutorial/) +* [NumPy tutorial](https://github.com/rougier/numpy-tutorial) *by Nicolas Rougier* +* [Stanford CS231](http://cs231n.github.io/python-numpy-tutorial/) *by Justin Johnson* * [NumPy User Guide](https://numpy.org/devdocs) **Books** -* [Guide to NumPy *by Travis E. Oliphant*](https://web.mit.edu/dvp/Public/numpybook.pdf) This is a free version 1 from 2006. For the latest copy (2015) see [here](https://dl.acm.org/doi/10.5555/2886196). -* [From Python to NumPy *by Nicolas P. Rougier*](https://www.labri.fr/perso/nrougier/from-python-to-numpy/) -* [Elegant SciPy](https://www.amazon.com/Elegant-SciPy-Art-Scientific-Python/dp/1491922877) *by Juan Nunez-Iglesias, Stéfan van der Walt, and Harriet Dashnow* +* [Guide to NumPy](https://web.mit.edu/dvp/Public/numpybook.pdf) *by Travis E. Oliphant* + This is the first and *free* edition of the book. To purchase the latest edition, + [click here](https://www.amazon.com/exec/obidos/ASIN/151730007X/acmorg-20). +* [From Python to NumPy](https://www.labri.fr/perso/nrougier/from-python-to-numpy/) + *by Nicolas P. Rougier* *(free)* +* [Elegant SciPy](https://www.amazon.com/Elegant-SciPy-Art-Scientific-Python/dp/1491922877) + *by Juan Nunez-Iglesias, Stéfan van der Walt, and Harriet Dashnow* -You may also want to check out the [Goodreads list](https://www.goodreads.com/shelf/show/python-scipy) on the subject of "Python+SciPy." Most books there are about the "SciPy ecosystem," which has NumPy at its core. +You may also want to check out the [Goodreads list](https://www.goodreads.com/shelf/show/python-scipy) +on the subject of "Python+SciPy." Most books there are about the "SciPy ecosystem," +which has NumPy at its core. **Videos** @@ -44,20 +57,30 @@ Try these advanced resources for a better understanding of NumPy concepts like a **Tutorials** -* [100 NumPy Exercises](http://www.labri.fr/perso/nrougier/teaching/numpy.100/index.html) *by Nicolas P. Rougier* -* [An Introduction to NumPy and Scipy](https://engineering.ucsb.edu/~shell/che210d/numpy.pdf) *by M. Scott Shell* -* [Numpy Medkits](http://mentat.za.net/numpy/numpy_advanced_slides/) *by Stéfan van der Walt* -* [NumPy Tutorials](https://numpy.org/numpy-tutorials) A collection of tutorials and educational materials in the format of Jupyter Notebooks developed and maintained by the NumPy Documentation team. To submit your own content, visit the [numpy-tutorials repository on GitHub](https://github.com/numpy/numpy-tutorials). +* [100 NumPy Exercises](http://www.labri.fr/perso/nrougier/teaching/numpy.100/index.html) + *by Nicolas P. Rougier* +* [An Introduction to NumPy and Scipy](https://engineering.ucsb.edu/~shell/che210d/numpy.pdf) + *by M. Scott Shell* +* [Numpy Medkits](http://mentat.za.net/numpy/numpy_advanced_slides/) + *by Stéfan van der Walt* +* [NumPy Tutorials](https://numpy.org/numpy-tutorials) A collection of tutorials and educational + materials in the format of Jupyter Notebooks developed and maintained by the NumPy Documentation team. + To submit your own content, visit the [numpy-tutorials repository on GitHub](https://github.com/numpy/numpy-tutorials). **Books** -* [Python Data Science Handbook](https://www.amazon.com/Python-Data-Science-Handbook-Essential/dp/1098121228) *by Jake Vanderplas* -* [Python for Data Analysis](https://www.amazon.com/Python-Data-Analysis-Wrangling-Jupyter/dp/109810403X) *by Wes McKinney* -* [Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy, and Matplotlib](https://www.amazon.com/Numerical-Python-Scientific-Applications-Matplotlib/dp/1484242459) *by Robert Johansson* +* [Python Data Science Handbook](https://www.amazon.com/Python-Data-Science-Handbook-Essential/dp/1098121228) + *by Jake Vanderplas* +* [Python for Data Analysis](https://www.amazon.com/Python-Data-Analysis-Wrangling-Jupyter/dp/109810403X) + *by Wes McKinney* +* [Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy, + and Matplotlib](https://www.amazon.com/Numerical-Python-Scientific-Applications-Matplotlib/dp/1484242459) + *by Robert Johansson* **Videos** -* [Advanced NumPy - broadcasting rules, strides, and advanced indexing](https://www.youtube.com/watch?v=cYugp9IN1-Q) *by Juan Nunez-Iglesias* +* [Advanced NumPy - broadcasting rules, strides, and advanced indexing](https://www.youtube.com/watch?v=cYugp9IN1-Q) + *by Juan Nunez-Iglesias* ***