In the last couple of years we have witnessed an enormous increase of machine learning (ML) applications. More and more program functions are no longer written in code, but learnt from a huge amount of data samples using an ML algorithm. However, what is often overlooked is the complexity of managing the resulting ML models as well as bringing these into a real production system. In software engineering, we have spent decades on developing tools and methodologies to create, manage and assemble complex software modules. We present an overview of current techniques to manage complex software, and how this applies to ML models.

翻译：在过去的几年里,我们目睹了机器学习应用的大量增加。 越来越多的程序功能不再以代码写成,而是从大量数据样本中学习的。 然而,人们经常忽视的是管理由此产生的ML模型以及将这些模型纳入一个真正的生产系统的复杂性。 在软件工程方面,我们花了数十年时间开发工具和方法来创建、管理和组装复杂的软件模块。我们概述了管理复杂软件的当前技术,以及这些技术如何适用于ML模型。