星期四:支持AutoML的网络平台

Chase D. Carthen, Christopher Lewis, Vinh D. Le, A. Tavakkoli, Frederick Harris, S. Dascalu
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引用次数: 0

摘要

THURSDAY是一个网络平台,通过提供易于访问的工具来帮助用户构建机器学习模型,这些工具可以手动创建模型,也可以通过使用AutoKeras等自动机器学习(AutoML)库来创建模型。作为周四关键创新的一部分,用户有机会配置和运行多个机器学习模型。然后可以将这些模型执行的结果与内置的性能指标进行比较。最后,THURSDAY允许用户分析超参数更改,以及AutoML库创建的更改,以便提供一个重要的工具,帮助修改现有模型。为了满足机器学习的高容量需求,周四采用了一种基于微服务的设计模式,支持容器化、编排和可扩展性。本文详细探讨了周四系统的设计、实现和影响。为了评估THURSDAY的能力,将其核心功能与提供机器学习支持的类似平台进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
THURSDAY: A Web Platform to Support AutoML
THURSDAY is a web platform that aids users in building machine learning models by providing easily accessible tools to either create models manually, or through the use of automated machine learning (AutoML) libraries like AutoKeras. As part of THURSDAY’s key innovations, users are given the opportunity to configure and run multiple machine learning models. The results of these model executions can then be compared with built-in performance metrics. Finally, THURSDAY allows users to analyze hyperparameter changes, as well as the changes created by AutoML libraries, in order to provide a vital tool that aids in the revision of existing models. To meet the high volume demands of machine learning, THURDAY adopted a microservice-based design pattern that supports containerization, orchestration, and scalabability. In this paper, the design, implementation, and impact of the THURSDAY system is explored in detail. In order to evaluate the capability of THURSDAY, its core functionality is compared against similar platforms that provide machine learning support.
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