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Large scale non-linear learning on a single CPU
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big_apple_py
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pygotham_2015
--room room705 10053 --force
Next: 11 The Python Datamodel: When and how to write objects
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Marks
Author(s):
Andreas Mueller
Location
Room 705
Date
aug Sun 16
Days Raw Files
Start
15:30
First Raw Start
15:25
Duration
00:25:00
Offset
0:04:24
End
15:55
Last Raw End
15:59
Chapters
00:00
0:22:14
Total cuts_time
25 min.
https://pygotham.org/2015/talks/146/large-scale-non-linear-learning-on-a-single-cpu
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This talk presents several methods for learning non-linear models on a single machine, where the dataset does not fit into ram. It will cover the hashing trick, kernel approximations, neural networks, and extreme learning machines (random neural networks). This will be a fairly technical talk, showing off some of the lesser known out-of-core capabilities of scikit-learn.
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2015-08-16/15_25_36.dv
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15:25:36 - 15:34:16 ( 00:08:40 )
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15:25:36
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15:34:16
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2015-08-16/15_34_17.dv
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15:34:17 - 15:56:31 ( 00:22:14 )
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15:34:17
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2015-08-16/15_56_32.dv
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2015-08-16/15_56_32.dv
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