Chapter 10: AutoML in the Enterprise

"Harnessing machine learning can be transformational, but for it to be successful, enterprises need leadership from the top. This means understanding that when machine learning changes one part of the business — the product mix, for example — then other parts must also change. This can include everything from marketing and production to supply chain, and even hiring and incentive systems."

– Erik Brynjolfsson, Director of the MIT Initiative on the Digital Economy

Automated Machine Learning (ML) is an enabler and an accelerator that unleashes the promise for organizations to expedite the analytics life cycle without having data scientists as a bottleneck. In earlier chapters, you learned how to perform automated ML using multiple hyperscalers, including open source tools, AWS, Azure, and GCP.

This chapter, however, is quite different since here we will explore the enterprise use of automated ML. We will look...