Recent advances in derivative-free optimization allow efficient approximation of the global-optimal solutions of sophisticated functions, such as functions with many local optima, non-differentiable and non-continuous functions. This article describes the ZOOpt (Zeroth Order Optimization) toolbox that provides efficient derivative-free solvers and is designed easy to use. ZOOpt provides single-machine parallel optimization on the basis of python core and multi-machine distributed optimization for time-consuming tasks by incorporating with the Ray framework -- a famous platform for building distributed applications. ZOOpt particularly focuses on optimization problems in machine learning, addressing high-dimensional and noisy problems such as hyper-parameter tuning and direct policy search. The toolbox is maintained toward a ready-to-use tool in real-world machine learning tasks.

翻译：最近在无衍生物优化方面的进展使得能够有效地接近全球最优化的复杂功能解决方案,例如许多本地opima、无差异和非连续性功能的功能。本篇文章描述了ZOOPT(Zeroth Aorder Apptimination)工具箱,提供高效的无衍生物解决方案,便于使用。ZOOPT提供单机平行优化,其依据是Python核心和多机分布优化,用于耗时任务,与Ray框架相结合 -- -- 这是建构分布式应用程序的著名平台。ZOOPT特别侧重于机器学习中的优化问题,解决高维度和吵闹的问题,如超参数调换和直接政策搜索。该工具箱被维持在现实世界机器学习任务中,成为现成的工具。