scholich / python-overview

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Overview

You can find Rabea's introduction notebook here: Introduction to python.

A more extensive introduction by Rick Muller, Sandia National Laboratories is the Crash Course in Python that is also contained in this repository. You can download and run/execute it on your computer directly.

Also, there is a list of Useful libraries for data science in Python.

You may also find an introductory example recognizing handwritten digits using scikit-image and scikit-learn.

Marko Popovich provided a notebook with an introduction to pandas.

There is also a notebook explaining how to speed-up parts of python code using Numba, Cython or parallel strategies.

If you need help setting something up or have other questions or suggestions, feel free to send me an email.

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