In the final episode of our Azure ML series, we’re joined by Erez Barak, Partner Group Manager of Azure ML at Microsoft.
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Erez’s group is currently focused on AutoML, and if AutoML is something you’re interested in, this is the talk for you. In our conversation, Erez gives us a full breakdown of his AutoML philosophy, including how he defines “true AutoML” and his take on the AutoML space, its role and its importance. We also discuss in great detail the application of AutoML as a contributor to the end-to-end data science process, which Erez breaks down into 3 key areas; Featurization, Learner/Model Selection, and Tuning/Optimizing Hyperparameters. Finally, we discuss post-deployment AutoML use cases and other areas under the AutoML umbrella that are generating excitement.
Thanks to our sponsor!
I’d like to thank Microsoft for their support of the show, and their sponsorship of this series. Thanks to decades of breakthrough research and technology, Microsoft is making AI real for businesses with Azure AI, a set of services that span vision, speech, language processing, custom machine learning, and more. Millions of developers and data scientists around the world are using Azure AI to build innovative applications and machine learning models for their organizations, including 85% of the Fortune 100. Microsoft customers like Spotify, Lexmark and Airbus choose Azure AI because of its proven enterprise-grade capabilities and innovations, wide range of developer tools and services, and trusted approach. Stay tuned to learn how Microsoft is enabling developers, data scientists, and MLOps and DevOps professionals across all skill levels to increase productivity, operationalize models at scale and innovate faster and more responsibly with Azure Machine Learning.
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Mentioned in the Interview
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“More On That Later” by Lee Rosevere licensed under CC By 4.0