Scaling Machine Learning with Spark: Distributed ML with MLlib, TensorFlow, and PyTorch (Grayscale Indian Edition)(Paperback, Adi Polak) | Zipri.in
Scaling Machine Learning with Spark: Distributed ML with MLlib, TensorFlow, and PyTorch (Grayscale Indian Edition)(Paperback, Adi Polak)

Scaling Machine Learning with Spark: Distributed ML with MLlib, TensorFlow, and PyTorch (Grayscale Indian Edition)(Paperback, Adi Polak)

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All Indian Reprints of O'Reilly are Printed in Grayscale.Learn how to build end-to-end scalable machine learning solutions with Apache Spark. 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.Scaling Machine Learning with Spark examines several technologies for building end-to-end distributed ML workflows based on the Apache Spark ecosystem with Spark MLlib, MLflow, TensorFlow, and PyTorch. If you're a data scientist who works with machine learning, this book shows you when and why to use each technology.