面向快速发展的工业应用的全栈机器学习环境

2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA) Pub Date : 2021-10-06 DOI:10.1109/DSAA53316.2021.9564174

Kayla Robinson, C. Billman, Muktesh Masih, Kevin Rose, Xi Wang, K. Hundman

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引用次数: 2

摘要

开发、部署和维护机器学习模型是许多数据科学团队的关键功能。我们描述了一个由美国家庭保险公司建立的框架来模拟财产的风险概况。通过实证实验，我们证明了我们的自动化端到端框架为商业环境中的实验和生产提供了一个快速的平台。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Full-Stack Machine Learning Environment for Rapidly Evolving Industry Applications

Developing, deploying, and maintaining machine learning models is a key function of many data science teams. We describe a framework built by American Family Insurance to model the risk profiles of properties. Through empirical experiments, we demonstrate that our automated, end-to-end framework provides a rapid platform for experimentation and productionalization in a business environment.

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来源期刊

2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)

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