Talk demonstrating how to massively optimise data processing and numerical computation in Python. We perform outlier detection on a large time-series weather dataset (ISD). We take detecting outliers in 600GBs worth of data in Python down from 28 days to 38 minutes.

Topics covered:

• motivations for fast numerical processing in Python
• why Python is a slow programming language
• fast numerical processing in numpy
• vectorisation
• using numba to optimise non-vectorised code
• parallelising computation using joblib

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