Machine learning is all around us today. But data scientists and IT teams tasked with creating models have a hard time bringing together the right mix of ingredients—from data, infrastructure, tools, and APIs—to do their jobs effectively.

Google’s Cloud ML Engine eases many of the challenges data scientists and IT teams face. It’s a managed service that allows businesses to build and deploy their own models using any type or any size of data.

With Google’s Cloud ML Engine, data scientists can create models for training and prediction. And it provides APIs for these two building blocks.

Nikhil Kothari, Senior Staff Software Engineer, Google Cloud, breaks down Google’s Cloud ML Engine. He shows you how to use it as a service, so that data scientists can focus on data and on building models instead of managing infrastructure.