> For the complete documentation index, see [llms.txt](https://www.mlcompendium.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.mlcompendium.com/experimental-design/contextual-bandits.md).

# Contextual Bandits

1. [Contextual bandits](https://drive.google.com/file/d/1EiLlajcSanTE19BOFKOTOlzHJxYSxz7w/view) via [personalization in practice](https://booking.ai/personalization-in-practice-2bb4bc680eb3) - 

## Tools

1. [contextualbandits.com](https://www.contextualbandits.com/) - adapt your creative according to context and outcomes automatically without A/B-sitting your campaigns.
2. [Striatum](https://github.com/ntucllab/striatum) - contextual bandits in python
3. [Contextual bandits](https://github.com/david-cortes/contextualbandits) In python by david cortes - "This Python package contains implementations of methods from different papers dealing with contextual bandit problems, as well as adaptations from typical multi-armed bandits strategies. It aims to provide an easy way to prototype and compare ideas, to reproduce research papers that don't provide easily-available implementations of their proposed algorithms, and to serve as a guide in learning about contextual bandits. For details about the implementations, or if you would like to cite this in your research, see ["Adapting multi-armed bandits policies to contextual bandits scenarios"](https://arxiv.org/abs/1811.04383)."\
   \ <img src="/files/TXP0NJualwoR7xbdKCzW" alt="" data-size="original">
4.


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