Your go-to online machine learning library

Vowpal Wabbit is a fast and flexible learning system that empowers you to test and explore real data and find meaningful outcomes to real problems.

Expand the boundaries of
online machine learning

Vowpal Wabbit is sponsored by Microsoft Research and influenced by a growing ecosystem of community contributions, academic research, and proven algorithms. It provides fast, efficient, and flexible online machine learning techniques for reinforcement learning, supervised learning, and more.

Optimize rewards with Contextual Bandits

Contextual Bandits are a form of reinforcement learning(RL). The vast majority of production real-world RL systems prefer contextual bandits techniques.

For an overview of a contextual bandit problem and how to use Vowpal Wabbit in a CB setting with Python.

Install Vowpal Wabbit

For more information on installation requirements, building Vowpal Wabbit from source, or using a package manager read the installation wiki. Additional binary packages are available for select platforms.
Select a configuration
* Configuration coming soon
Run this command
Ready to use Vowpal Wabbit? Follow this getting started tutorial . You will learn how to perform Linear Regression with VW—including how to interact with VW by structuring input and learning how to interpret VW output.

A vehicle for machine learning research

Vowpal Wabbit’s design and capabilities are informed and influenced by advanced research and proven algorithms. Researchers who wish to implement their algorithm in Vowpal Wabbit have access to quick deployment and extensive use.

Visit our publications list for more details on the research driving Vowpal Wabbit.

Join our community

Vowpal Wabbit is the result of community contributions since 2007. Get involved by contributing code or documentation on GitHub. Get answers to your questions on StackOverflow or chat with the development community on Gitter.
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