TensorFlow and Keras are popular libraries for machine learning because of their support for deep learning and GPU deployment. Join Ron Bodkin and Brian Foo to learn how to execute these libraries in production with vision and recommendation models and how to export, package, deploy, optimize, serve, monitor, and test models using Docker and TensorFlow Serving in Kubernetes.
Ron Bodkin is a technical director on the applied artificial intelligence team at Google, where he provides leadership for AI success for customers in Google’s Cloud CTO office. Ron engages deeply with Global F500 enterprises to unlock strategic value with AI, acts as executive sponsor with Google product and engineering to deliver value from AI solutions, and leads strategic initiatives working with customers and partners. Previously, Ron was the founding CEO of Think Big Analytics, a company that provides end-to-end support for enterprise big data, including data science, data engineering, advisory, and managed services and frameworks such as Kylo for enterprise data lakes. When Think Big was acquired by Teradata, Ron led global growth, the development of the Kylo open source data lake framework, and the company’s expansion to architecture consulting; he also created Teradata’s artificial intelligence incubator.
Brian Foo is a senior software engineer for Google Cloud working on applied artificial intelligence, where he builds demos for Google Cloud’s strategic customers and creates open source tutorials to improve public understanding of AI. Previously, Brian worked at Uber, where he trained machine learning models and built a large-scale training and inference pipeline for mapping and sensing/perception applications using Hadoop and Spark, and headed the real-time bidding optimization team at Rocket Fuel, where he worked on algorithms that determined millions of ads shown every second across many platforms such as web, mobile, and programmatic TV. Brian holds a BS in EECS from UC Berkeley and a PhD in EE telecommunications from UCLA.
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