Putting machine learning into production in the enterprise is not easy: Many organizations are struggling to implement the technology at scale. But it is possible to make the process of building, scaling, and deploying enterprise machine learning solutions repeatable and predictable.

In this on-demand webinar, Tom Davenport, President’s Distinguished Professor of IT and Management, Babson College; Alex Breshears, senior product manager, Production Machine Learning, Cloudera; and Abbie Lundberg, business technology analyst, Lundberg Media discuss the specific challenges enterprises face in machine learning and how they can create an end-to-end, factory-like capability.

In this free webinar, you will learn:

• What challenges to expect in machine learning production and scaling.

• Why you’ll need to rethink organizational structure for effective cross-functional work.

• How software development and deployment processes need to change in order to extend them to machine learning.

• The importance of a robust data pipeline for AI and what it takes to develop it.

Tom Davenport
Tom Davenport

President’s Distinguished Professor of IT and Management, Babson College

Alex Breshears
Alex Breshears

Senior product manager, Production Machine Learning, Cloudera

Abbie Lundberg
Abbie Lundberg

Business technology analyst, Lundberg Media

The content was created by the speakers of this event. The MIT Sloan Management Review editorial staff was not involved in the selection, development, or broadcast of this event.

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“How to Scale Production Machine Learning in the Enterprise”

On Demand