Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/29g799t. John Langford discusses how to use Vowpal Wabbit in and as a machine learning system including architecture, unique capabilities, and applications. He goes into detail about the use in the context of a decision service for personalized news recommendation. Filmed at qconnewyork.com. John Langford is a machine learning research scientist. He works at Microsoft Research New York, of which he was one of the founding members, and was previously affiliated with Yahoo! Research, Toyota Technological Institute, and IBM's Watson Research Center. He was the program co-chair for the 2012 International Conference on Machine Learning.

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Watch the video with slide
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vowpal-wabbit

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4. 1 1 5 4 3
7 5 3 5 3
5 5 9 0 6
3 5 2 0 0

5.  Run ML algorithm

6.  Gather your data
 Label your data
 Run ML algorithm
 Embed into larger system
Can we make it easier?

8. Ex: Which news?
Repeatedly:
1. Observe features of user+articles
2. Choose a news article.
3. Observe click-or-not
Goal: Maximize fraction of clicks

9. Contextual Bandits
Repeatedly:
1. Observe features
2. Choose action ∈
3. Observe reward
Goal: Minimize regret to a set of
policies.

11. Policy

12. Policy
Randomization

13. Policy
Randomization

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16. ExploreExplore
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What could possibly go wrong?

17. Client Library
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Server
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Policy
App
context
decision
reward
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18. Client Library
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Online
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Policy
App
context
decision
reward
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Explore

19. Client Library
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Server
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Learning
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Policy
App
context
decision
reward
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Policy
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context
decision
reward
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21. Client Library
Or Web API
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Learning
Policy
App
context
decision
reward
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Deploy

22. Client Library
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Server
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App
context
decision
reward
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Learn
Data

25. …
> 25% increase in
clicks
(without much tuning)

27. 1) Interactive
Learning
ExploreExplore
LogLogLearnLearn
DeployDeploy

33. Watch the video with slide synchronization on
InfoQ.com!
https://www.infoq.com/presentations/vowpal-
wabbit