Learning Ray: Flexible Distributed Python for Machine Learning
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OReilly Media
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Max is a data science professor and software engineer located in Hamburg, Germany. Hes an active open source contributor, maintainer of several Python packages, author of machine learning books and speaker at international conferences. As head of product research at Pathmind Inc. hes developing reinforcement learning solutions for industrial applications at scale using Ray. Pathmind works closely with the AnyScale team and is a power user of Rays RLlib, Tune and Serve libraries. Max has been a core developer of DL4J at Skymind, helped grow and extend the Keras ecosystem, and is a hyperopt maintainer.
Edward Oakes ([email protected]), writing chapters 7 (data) & 9 (serving): "Edward is a software engineer and team lead at Anyscale, where he leads the development of Ray Serve and is one of the top open source contributors to Ray. Prior to Anyscale, he was a graduate student in the EECS department at UC Berkeley."
RIchard Liaw ([email protected]), writing chapters 6 (training) & 8 (clusters): Richard Liaw is a software engineer at Anyscale, working on open source tools for distributed machine learning. He is on leave from the PhD program at the Computer Science Department at UC Berkeley, advised by Joseph Gonzalez, Ion Stoica, and Ken Goldberg.
Edward Oakes ([email protected]), writing chapters 7 (data) & 9 (serving): "Edward is a software engineer and team lead at Anyscale, where he leads the development of Ray Serve and is one of the top open source contributors to Ray. Prior to Anyscale, he was a graduate student in the EECS department at UC Berkeley."
RIchard Liaw ([email protected]), writing chapters 6 (training) & 8 (clusters): Richard Liaw is a software engineer at Anyscale, working on open source tools for distributed machine learning. He is on leave from the PhD program at the Computer Science Department at UC Berkeley, advised by Joseph Gonzalez, Ion Stoica, and Ken Goldberg.
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