Scientific Python

Python has become one of the cornerstone languages for developing scientific software, thanks to its flexibility, extensibility, ease of use and extensive ecosystem. Whether you’re doing machine learning, processing & visualising data, or running a statistical analysis, there’s a good chance there’s a Python package that can help get you to a result quickly.

This track is for anyone using Python for scientific computing - be it data analysis, engineering, academic research, statistics, modelling systems, machine learning, or just generally hacking together new tools to extract insight.

Tell us what you are doing with Python in science. What insights, challenges, quirks, and innovations have you encountered?

This year, PyCon AU is partnering with the Journal of Open Source Software (JOSS) to publish academic papers in association with PyCon AU submissions. If you are interested, see here for more information.