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Practical Machine Learning Spark by Gupta Gourav (14 results)
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Practical Machine Learning with Spark: Uncover Apache Spark's Scalable Performance with High-Quality Algorithms Across NLP, Computer Vision and ML (En (Paperback or Softback)
Published by Bpb Publications 10/17/2022, 2022
ISBN 10: 939139213X ISBN 13: 9789391392130
Language: English
Paperback or Softback. Condition: New. Practical Machine Learning with Spark: Uncover Apache Spark's Scalable Performance with High-Quality Algorithms Across NLP, Computer Vision and ML (En 1.87. Book.
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£ 37.15
Convert currency£ 7.51 shipping from Canada to U.S.A.Quantity: Over 20 available
Add to basketpaperback. Condition: New. Special order direct from the distributor.
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Practical Machine Learning with Spark: Uncover Apache Spark's Scalable Performance with High-Quality Algorithms Across NLP, Computer Vision and ML (En
Published by BPB Publications 2022-10, 2022
ISBN 10: 939139213X ISBN 13: 9789391392130
Language: English
£ 31.65
Convert currency£ 15.49 shipping from United Kingdom to U.S.A.Quantity: 10 available
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Practical Machine Learning with Spark: Uncover Apache Spark's Scalable Performance with High-Quality Algorithms Across NLP, Computer Vision and ML (English Edition)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Add to basketCondition: Hervorragend. Zustand: Hervorragend | Seiten: 500 | Sprache: Englisch | Produktart: Bücher.
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Practical Machine Learning with Spark
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Add to basketPAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Explore the cosmic secrets of Distributed Processing for Deep Learning applications. KEY FEATURES ¿In-depth practical demonstration of ML/DL concepts using Distributed Framework. ¿ Covers graphical illustrations and visual explanations for ML/DL pipelines. ¿ Includes live codebase for each of NLP, computer vision and machine learning applications. DESCRIPTION This book provides the reader with an up-to-date explanation of Machine Learning and an in-depth, comprehensive, and straightforward understanding of the architectural techniques used to evaluate and anticipate the futuristic insights of data using Apache Spark. The book walks readers by setting up Hadoop and Spark installations on-premises, Docker, and AWS. Readers will learn about Spark MLib and how to utilize it in supervised and unsupervised machine learning scenarios. With the help of Spark, some of the most prominent technologies, such as natural language processing and computer vision, are evaluated and demonstrated in a realistic setting. Using the capabilities of Apache Spark, this book discusses the fundamental components that underlie each of these natural language processing, computer vision, and machine learning technologies, as well as how you can incorporate these technologies into your business processes. Towards the end of the book, readers will learn about several deep learning frameworks, such as TensorFlow and PyTorch. Readers will also learn to execute distributed processing of deep learning problems using the Spark programming language. WHAT YOU WILL LEARN ¿ Learn how to get started with machine learning projects using Spark. ¿ Witness how to use Spark MLib's design for machine learning and deep learning operations. ¿ Use Spark in tasks involving NLP, unsupervised learning, and computer vision. ¿ Experiment with Spark in a cloud environment and with AI pipeline workflows. ¿ Run deep learning applications on a distributed network. WHO THIS BOOK IS FOR This book is valuable for data engineers, machine learning engineers, data scientists, data architects, business analysts, and technical consultants worldwide. It would be beneficial to have some familiarity with the fundamentals of Hadoop and Python.
