In the recent years, machine learning has made great advancements that have
been at the root of many breakthroughs in different application domains.
However, it is still an open issue how make them applicable to high-st
本文提供了一个适用于企业的机器学习模型生命周期管理成熟度框架,旨在解决为 AI 应用定义业务用例、将业务需求转化为数据科学家的数据需求、连续提高 AI 应用程序的准确度和公平性,以及专门针对特定情况定制通用机器学习模型等方面的问题。该框架重新解释了软件能力成熟度模型,并提出了许多最佳实践,可以帮助企业在不考虑其起点的情况下实现更高的成熟度水平。