 | |
 A screenshot of Vowpal Wabbit | |
| Developer(s) | Yahoo! Research & later Microsoft Research |
|---|---|
| Stable release | 9.6.0
/ November 8, 2022 |
| Repository | github |
| Written in | C++ |
| Operating system | Linux, macOS, Microsoft Windows |
| Platform | Cross-platform |
| Type | Machine learning |
| License | BSD License |
| Website | vowpalwabbit |
Vowpal Wabbit (VW) is an open-source fast online interactive machine learning system library and program developed originally at Yahoo! Research, and currently at Microsoft Research. It was started and is led by John Langford. Vowpal Wabbit's interactive learning support is particularly notable including Contextual Bandits, Active Learning, and forms of guided Reinforcement Learning. Vowpal Wabbit provides an efficient scalable out-of-core implementation with support for a number of machine learning reductions, importance weighting, and a selection of different loss functions and optimization algorithms.