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WAX-ML: A Python library for machine learning and feedback loops on streaming data

Machine Learning 2021-06-14 v1 Computation and Language

Abstract

Wax is what you put on a surfboard to avoid slipping. It is an essential tool to go surfing... We introduce WAX-ML a research-oriented Python library providing tools to design powerful machine learning algorithms and feedback loops working on streaming data. It strives to complement JAX with tools dedicated to time series. WAX-ML makes JAX-based programs easy to use for end-users working with pandas and xarray for data manipulation. It provides a simple mechanism for implementing feedback loops, allows the implementation of online learning and reinforcement learning algorithms with functions, and makes them easy to integrate by end-users working with the object-oriented reinforcement learning framework from the Gym library. It is released with an Apache open-source license on GitHub at https://github.com/eserie/wax-ml.

Keywords

Cite

@article{arxiv.2106.06524,
  title  = {WAX-ML: A Python library for machine learning and feedback loops on streaming data},
  author = {Emmanuel Sérié},
  journal= {arXiv preprint arXiv:2106.06524},
  year   = {2021}
}

Comments

12 pages, 7 figures

R2 v1 2026-06-24T03:06:44.045Z