AutoML platforms push data science projects to the finish line

Since businesses often don't have the time or resources to support the long and tedious work required to complete data science projects, most of them never come to fruition. The fairly recent development of automated machine learning, or AutoML, rectifies this by speeding up the work data scientists perform through automation. Dennis Michael Sawyers, data scientist and author of Automated Machine Learning with Microsoft Azure, uses Azure's AutoML product as the foremost example of how automated ML software expedites and simplifies this otherwise arduous work. In this Q&A, Sawyers discusses the evolution of automated machine learning platforms and how they are used to develop ML models. Editor's note: The following interview was edited for length and clarity.