Creating a Data-Driven Culture at ADP with Jack Berkowitz

800 800 The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

About This Episode

Today we continue our 2021 re:Invent series joined by Jack Berkowitz, chief data officer at ADP. In our conversation with Jack, we explore the ever evolving role and growth of machine learning at the company, from the evolution of their ML platform, to the unique team structure. We discuss Jack’s perspective on data governance, the broad use cases for ML, how they approached the decision to move to the cloud, and the impact of scale in the way they deal with data. Finally, we touch on where innovation comes from at ADP, and the challenge of getting the talent it needs to innovate as a large “legacy” company.

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Thanks to our Sponsor!

I want to send a huge thanks once again to our friends at Amazon Web Services for their support of the podcast and their sponsorship of this year’s re:Invent series.

AWS offers a broad array of services and infrastructure at all three layers of the machine learning technology stack, ranging from high performance compute instances running the latest GPUs and custom-designed silicon for training and inference, to the Amazon SageMaker family of services that allows data scientists and developers to quickly build, train, and deploy high-quality models, to a full complement of AI services for use cases like demand forecasting, fraud prevention, personalized recommendations, document analysis, and much more.

More than 100,000 customers trust AWS for Machine Learning, and the company aims to put machine learning in the hands of every developer, data scientist and enthusiast with newly announced offerings like Amazon SageMaker Studio Lab which offers free JupyterLab Notebooks, GPU Compute and Storage for your machine learning projects.

To learn more about AWS machine learning services, and how they’re helping customers accelerate their machine learning journeys, visit aws.amazon.com/machine-learning/

And also be sure to check out studiolab.sagemaker.aws to sign up for SageMaker Studio Lab.

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