Pinned Repositories
coba
Contextual bandit benchmarking
docker-images
Docker images used for continuous integration
estimators
Estimators to perform off-policy evaluation
jupyter-notebooks
Vowpal Wabbit examples and tutorials
learn_to_pick
A python library for online learning in RL loops, specialized for Contextual Bandit scenarios. Choose actions from multiple options, evaluate decisions, and integrate feedback for improved future outcomes. Features versatile scoring, advanced featurization, and configurable learning policies.
neurips2019
py-vowpal-wabbit-next
Experimental new Python bindings for the VowpalWabbit library
reinforcement_learning
Interaction-side integration library for Reinforcement Learning loops: Predict, Log, [Learn,] Update
vowpal_wabbit
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
workshop
Vowpal Wabbit's Repositories
VowpalWabbit/vowpal_wabbit
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
VowpalWabbit/reinforcement_learning
Interaction-side integration library for Reinforcement Learning loops: Predict, Log, [Learn,] Update
VowpalWabbit/coba
Contextual bandit benchmarking
VowpalWabbit/jupyter-notebooks
Vowpal Wabbit examples and tutorials
VowpalWabbit/estimators
Estimators to perform off-policy evaluation
VowpalWabbit/py-vowpal-wabbit-next
Experimental new Python bindings for the VowpalWabbit library
VowpalWabbit/docker-images
Docker images used for continuous integration
VowpalWabbit/workshop
VowpalWabbit/data-science
VowpalWabbit/learn_to_pick
A python library for online learning in RL loops, specialized for Contextual Bandit scenarios. Choose actions from multiple options, evaluate decisions, and integrate feedback for improved future outcomes. Features versatile scoring, advanced featurization, and configurable learning policies.
VowpalWabbit/neurips2019
VowpalWabbit/rl_chain
VowpalWabbit/slates-experiments
VowpalWabbit/docs
Genenerated documentation
VowpalWabbit/icml2019
VowpalWabbit/slope-experiments
VowpalWabbit/vowpalwabbit.github.io
Official website of Vowpal Wabbit
VowpalWabbit/ccb-experiments
VowpalWabbit/feature-broker
Mature software applications are highly componentized and have well-defined API boundaries among components. This structure leads to constraints making in-process inference challenging due to the difficulty of access to features. The FeatureBroker library presents a solution to this problem. This helped with adoption of VW in inference. We believe that this is a pervasive problem. The goal of open sourcing this library is to reduce the developer friction in adopting VW in software stacks that are built with these constraints.
VowpalWabbit/agenda
VowpalWabbit/rl_loop_deployment
Deploy RL Loop in Azure
VowpalWabbit/rl_loop_image
VowpalWabbit/autogen
Enable Next-Gen Large Language Model Applications. Join our Discord: https://discord.gg/pAbnFJrkgZ
VowpalWabbit/langchain
⚡ Building applications with LLMs through composability ⚡