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.

翻译：Wax是您在冲浪板上放置的避免滑落的工具。 这是一个进行冲浪的基本工具。 我们引入了WAX-ML 一个面向研究的Python图书馆, 提供设计强大的机器学习算法和流数据反馈循环的工具。 它努力用时间序列专用工具来补充JAX。 WAX-ML 使基于JAX 的程序便于终端用户与pandas和xarray一起操作数据操作。 它为实施反馈回路提供了一个简单的机制, 使在线学习和强化带有功能的学习算法得以实施, 并使终端用户更容易与Gym 库的面向对象的强化学习框架融合。 它在https://github.com/eserie/wax-ml上, 与GitHub的Apache开放源许可证一起发布。