THIS COURSE IS STILL IN PREPARATION
Scientific NumPy
This course aims to give an overview over the basic tools provided by NumPy to work effciently with arrays, in any dimension, to lower your computation time and save storage.
For a full treatment of the topic or if you are looking for a specific use case we suggest looking on Numpy.org and the provided NumPy Quickstart tutorial. Stack overflow is also a very usefull platform to get tips and tricks using NumPy, and Python in general, and always a good starting point to solve problems and get answers to specific questions.
To work effienctly with arrays is the basis of any fast machine learning algorithm and therefore it is of great advantage to have same basic knowledge about NumPy and working with arrays.
The notebook theory-numpy-and-arrays summarizes a few usefull techniques, which can practiced in the exercise notebooks given in the list below.