Vowpal Wabbit is both an open-source machine learning toolkit and an active research platform. In this talk I introduce Vowpal Wabbit, discuss some of the design decisions, and the types of problems for which VW is (or is not) a good fit. The talk includes (live) demonstrations some of the latest features for recommendation, contextual bandit, and structured prediction problems.

1. VOWPAL WABBIT Paul Mineiro
O P E N
D A T A
S C I E N C E
C O N F E R E N C E_
BOSTON 2015
@opendatasci

3. https://github.com/JohnLangford/vowpal_wabbit/
http://azure.microsoft.com/en-us/services/machine-learning/

4. https://github.com/JohnLangford/vowpal_wabbit/
http://azure.microsoft.com/en-us/services/machine-learning/

6. quickly
giant
beyond classification

7. quickly

8. Online Learning
Progressive Validation Loss

9. Online Learning
Progressive Validation Loss

10. New features: lowering bias, increasing variance.
Regularizing: lowering variance.

11. giant

15. giant

16. might work poorly

17. might work poorly
matrix factorization

18. giant

20. hope for the best

21. beyond classification

22. beyond classification

23. beyond classification

26. Task Input Output
Image Segmentation
Machine Translation Ces deux principes se tiennent à
la croisée de la philosophie, de la
politique, de l’économie, de la
sociologie et du droit.
Both principles lie at the crossroads
of philosophy, politics, economics,
sociology, and law.
Syntactic Analysis The monster ate a big sandwich.
The monster ate a big sandwich.

28. exactly same code as

31. kill (James Earl Ray, Martin Luther King Junior)

33. Predict entities

34. Predict entities
Predict relations

35. Predict entities
Predict relations