Vowpal Wabbit
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Overview
HEALTH SCORE
Fair
62out of 100
Security posture drags the score down. Development cadence and maintainer coverage help keep it from falling further.
LIFECYCLE
Active
Consistent commits, responsive maintainers, regular releases, and healthy issue triage.
Health breakdown
Fair(62/100)
Maintainer availability, known risks and supply chain posture, and whether the project is actively developed or appropriately stable.
Maintainer responsiveness
Median response time is 1 day.
Bus factor
Only 2 active maintainers currently have merge rights.
Organization Diversity
Contributors span 29 organizations.
Project Achievements
Leaderboards
About
Vowpal Wabbit is a fast, efficient machine learning system library and command line tool that implements online learning algorithms, particularly for reinforcement learning, contextual bandits, and other interactive learning approaches. It focuses on speed, scalability, and real-world applications in areas like click-through rate prediction and natural language processing.
First commit
Software value
$8.2M
Tags
active-learning
c-plus-plus
contextual-bandits
cpp
learning-to-search
machine-learning
online-learning
reinforcement-learning
License(s)
Other
Data sources
Git
GitHub