Vowpal Wabbit

A Vowpal Wabbit is an open source out-of-core learning system library.

• AKA: VW.
  • Vowpal Wabbit, v8.7.0(~2019-06-06) [1]
  • Vowpal Wabbit, v8.3.1(~2016-12-29) [2]
  • Vowpal Wabbit, v8(~June 27, 2015).
  • …
• Counter-Example(s):
  • Tensorflow.
  • Spark.ML.
  • scikit-learn.
• See: Online Machine Learning, Machine Learning Reductions.

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References

• http://hunch.net/~vw/

2017

• (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/Vowpal_Wabbit Retrieved:2017-2-15.
  • Vowpal Wabbit (also known as "VW") is an open source fast out-of-core 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 is notable as an efficient scalable implementation of online machine learning and support for a number of machine learning reductions, importance weighting, and a selection of different loss functions and optimization algorithms.

2017

• https://github.com/JohnLangford/vowpal_wabbit/wiki/Tutorial
  • QUOTE:
    • Version 8.3 tutorial (at NIPS 2016) includes Contextual bandits, Logarithmic time classification, and Joint Prediction.
    • Version 8.1 tutorial (at NIPS 2015) includes Learning to search results + active learning + C# library + decision service

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