Scaling Machine Learning with Spark: Distributed ML with MLlib, TensorFlow, and

The Nile on eBay   Scaling Machine Learning with Spark by Adi Polak

With this practical guide, author Adi Polak introduces data and ML practitioners to creative solutions that supersede today's traditional methods. You'll learn a more holistic approach that takes you beyond specific requirements and organizational goals--allowing data and ML practitioners to collaborate and understand each other better.

FORMATPaperback LANGUAGEEnglish CONDITIONBrand New Publisher Description

Get up to speed on Apache Spark, the popular engine for large-scale data processing, including machine learning and analytics. If you're looking to expand your skill set or advance your career in scalable machine learning with MLlib, distributed PyTorch, and distributed TensorFlow, this practical guide is for you. Using Spark as your main data processing platform, you'll discover several open source technologies designed and built for enriching Spark's ML capabilities.Scaling Machine Learning with Spark examines various technologies for building end-to-end distributed ML workflows based on the Apache Spark ecosystem with Spark MLlib, MLFlow, TensorFlow, PyTorch, and Petastorm. This book shows you when to use each technology and why. If you're a data scientist working with machine learning, you'll learn how to:Build practical distributed machine learning workflows, including feature engineering and data formatsExtend deep learning functionalities beyond Spark by bridging into distributed TensorFlow and PyTorchManage your machine learning experiment lifecycle with MLFlowUse Petastorm as a storage layer for bridging data from Spark into TensorFlow and PyTorchUse machine learning terminology to understand distribution strategies

Author Biography

As Vice President of Developer Experience at Treeverse, Adi Polak shapes the future of data & ML technologies for hands-on builders. She also contributes to the lakeFS open-source, a git-like interface for object stores. In her work, Adi brings her vast industry research and engineering experience to bear in educating and helping teams design, architect, and build cost-effective data systems and machine learning pipelines that emphasize scalability, expertise, and business goals. Adi is a frequent worldwide presenter and the author of O'Reilly's upcoming book, "Machine Learning With Apache Spark." She is continually an invited member of multiple program committees and advisor for conferences like Data & AI Summit, Scale by the Bay, and others. Previously, Adi was a senior manager for Azure at Microsoft, where she focused on building advanced analytics systems and modern architectures. When Adi isn't building data pipelines or thinking up new software architecture, you can find her on the local cultural scene or at the beach.

Details ISBN1098106822 Author Adi Polak Short Title Scaling Machine Learning with Spark Pages 400 Publisher O'Reilly Media Language English Year 2023 ISBN-10 1098106822 ISBN-13 9781098106829 Format Paperback Audience General/Trade Imprint O'Reilly Media Place of Publication Sebastopol Country of Publication United States Subtitle Distributed ML with MLlib, TensorFlow, and PyTorch Publication Date 2023-03-21 AU Release Date 2023-03-21 NZ Release Date 2023-03-21 US Release Date 2023-03-21 UK Release Date 2023-03-21 DEWEY 006.312 We've got this

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