hands-on tutorial

Hands-on for 'Python - Multiprocessing' tutorial

The questions this addresses are:
- How can I parallelize code to make it run faster
- What code is, or is not, a prime target for parallelisation

The objectives are:
- Understanding how to paralellise code to make it run faster.
- Identifying how to decompose code into a parallel unit.

Licence: Creative Commons Attribution 4.0 International

Keywords: data-science, jupyter-notebook

Target audience: Students

Resource type: hands-on tutorial

Authors: Helena Rasche

Scientific topics: Software engineering


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