Wise.io: A Machine-Learning Platform (PyData SV 2013)
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Transcript of Wise.io: A Machine-Learning Platform (PyData SV 2013)
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Henrik Brink, CTO
PyData SV 2013, March 19
Machine Learning, Python and Raspberry Pi’s
@brinkar @wiseio
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11kly
11kx
Reference New Difference
Palomar Transient Factory (PTF) ~1.5 million candidates per night
~10 new transients
http://www.astro.caltech.edu/ptf/
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PTF11kly (SN 2011fe)
©Peter Nugent
Supernova Discovery in the Pinwheel Galaxy
11 hr after explosion
Nearest SN Ia in >3 decades
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Python Bootcamps at Berkeley
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Machine Learning in
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ML pain points I
• Data is messy!
• Hard to scale non-linear algorithms to large datasets
• Ad-hoc feature engineering
• Collaboration on data, features and models is difficult
data scientists
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Random Forest®Random Forest® is a registered trademark of Salford Systems
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Brink+2012
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Brink+2012
10% label noise
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bit.ly/YZZb9d
WiseRF™
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WiseRF™
12 GB MNIST in 90 seconds
8 core EC2 instance
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WiseRF™
A brain for the Internet of Things!
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Higher speeds
Larger datasets
Hadoop / Mahout
Energy sensorsAd bidding
Credit card fraud detection
Video tracking
Financial predictions
Batch product recommendations Real-time
recommendations
Internet of ThingsHealthcaresensors
Fast vs Scalable
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High-frequency data science
High-frequency prediction
Feature engineering
Data ingestion
Raw data
Model deployment
Model validation
High-frequency Machine Learning
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• Statistical validation of models
• Lack of feature engineering expertise
• Dealing with data and computing infrastructure
ML pain points IIapplication developers
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Machine Learning as a Service™
bit.ly/15eWEZG
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Reusable features
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Collaboration
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Integration
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docs.wise.io
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• Scalable infrastructure required
• Hard to go from data science experiments to production.
• Complete privacy / security.
ML pain points IIIbusiness and enterprise
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