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gptkbp:instance_of
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gptkb:machine_learning
|
|
gptkbp:can_be_used_for
|
gptkb:advertising
natural language processing
recommendation systems
search ranking
|
|
gptkbp:developed_by
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gptkb:Microsoft
|
|
gptkbp:first_released
|
gptkb:2007
|
|
gptkbp:has
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command line interface
active community
pre-trained models
extensive documentation
active development
Python bindings
Java bindings
various learning algorithms
|
|
https://www.w3.org/2000/01/rdf-schema#label
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Vowpal Wabbit
|
|
gptkbp:is_available_on
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gptkb:Git_Hub
|
|
gptkbp:is_compatible_with
|
gptkb:Linux
gptkb:mac_OS
gptkb:Windows
|
|
gptkbp:is_integrated_with
|
gptkb:Hadoop
gptkb:Spark
gptkb:Docker
|
|
gptkbp:is_known_for
|
flexibility
high scalability
ease of use
fast training times
|
|
gptkbp:is_open_source
|
gptkb:true
|
|
gptkbp:is_optimized_for
|
gptkb:Speed
memory efficiency
|
|
gptkbp:is_part_of
|
gptkb:Microsoft_Research
|
|
gptkbp:is_supported_by
|
gptkb:academic_research
community contributions
industry partnerships
|
|
gptkbp:is_used_by
|
gptkb:Yahoo
gptkb:e_Bay
gptkb:Facebook
|
|
gptkbp:is_used_for
|
fraud detection
anomaly detection
user personalization
A/ B testing
|
|
gptkbp:is_used_in
|
data science
machine learning competitions
|
|
gptkbp:provides
|
regression
multi-class classification
bandit learning
|
|
gptkbp:supports
|
online learning
multi-threading
distributed learning
large scale data
|
|
gptkbp:uses
|
feature hashing
|
|
gptkbp:written_in
|
gptkb:C
gptkb:C++
gptkb:Python
gptkb:Java_Script
|
|
gptkbp:bfsParent
|
gptkb:John_Langford
|
|
gptkbp:bfsLayer
|
6
|