In the last post we have explored how tsfresh
automatically extracts many time series features from your input data. We have also discussed two possibilities to speed up your feature extraction calculation: using multiple cores on your local machine (which is already tuned on by default) or distributing the calculation over a cluster of machines.
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In my last post in this series, we have developed all the building blogs for our data science application - we only miss the parallelisation setup.
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