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Machine Learning in Python - Gaussian Processes
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Author(s):
Philip Sterne
Location
Orange Room
Date
oct Fri 07
Days Raw Files
Start
13:30
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Duration
00:45:00
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None
End
14:15
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None min.
https://za.pycon.org/talks/39/
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Any time you have noisy data where you would like to see the underlying trend then you should think about using Gaussian processes. They will smooth out any noise and give you a great visualisation of the error bars as well. Rather than fitting a specific model to the data, Gaussian processes can model *any* smooth function. I will show you how to use Python to: - fit Gaussian Processes to data - display the results intuitively - handle large datasets This talk will gloss over mathematical detail and instead focus on the options available to the python programmer. There will be code posted to github beforehand so you can follow along in the talk, or just scoop up the useful bits afterwards.
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