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  • 1
    Online Resource
    Online Resource
    What's New In TensorFlow 2.x? (2020)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (107 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Since its 2015 release, TensorFlow has become a de facto standard among enterprise AI technologies. This comprehensive report introduces the new features of TensorFlow 2.x and Keras to developers and data scientists with machine learning skills. Many companies consider TensorFlow 2.x to be a major step in building a one-stop shop for deep learning tasks they need to perform. Romeo Kienzler, chief data scientist at the IBM Center for Open Source Data and AI Technologies, and Jerome Nilmeier, a data scientist and developer at Spark Technology Center, explain how your company can benefit from the new TensorFlow functionality. After reading this report, you can determine objectively whether adopting or upgrading to TensorFlow 2.x is worth your while. You'll examine: Two key TensorFlow APIs: Tensor-based API and Keras The eager execution mode for natural Python programming without TensorFlow sessions tf.function and AutoGraph for creating TensorFlow code in pure Python that the TensorFlow execution engine can consume How Keras is now tightly integrated with the TensorFlow backend under the hood The TensorBoard visualization framework, which contains rich capabilities How TensorFlow accomplishes parallel neural network training and scoring TensorFlow 2.x features including API cleanup, improved model export, and TensorFlow Serving
    Note: Online resource; Title from title page (viewed July 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 2
    Online Resource
    Online Resource
    Mastering Apache Spark 2.x : scalable analytics faster than ever (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785285226 , 178528522X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Data mining ; Information retrieval ; Electronic books ; Electronic books ; local
    Abstract: Advanced analytics on your Big Data with latest Apache Spark 2.x About This Book An advanced guide with a combination of instructions and practical examples to extend the most up-to date Spark functionalities. Extend your data processing capabilities to process huge chunk of data in minimum time using advanced concepts in Spark. Master the art of real-time processing with the help of Apache Spark 2.x Who This Book Is For If you are a developer with some experience with Spark and want to strengthen your knowledge of how to get around in the world of Spark, then this book is ideal for you. Basic knowledge of Linux, Hadoop and Spark is assumed. Reasonable knowledge of Scala is expected. What You Will Learn Examine Advanced Machine Learning and DeepLearning with MLlib, SparkML, SystemML, H2O and DeepLearning4J Study highly optimised unified batch and real-time data processing using SparkSQL and Structured Streaming Evaluate large-scale Graph Processing and Analysis using GraphX and GraphFrames Apply Apache Spark in Elastic deployments using Jupyter and Zeppelin Notebooks, Docker, Kubernetes and the IBM Cloud Understand internal details of cost based optimizers used in Catalyst, SystemML and GraphFrames Learn how specific parameter settings affect overall performance of an Apache Spark cluster Leverage Scala, R and python for your data science projects In Detail Apache Spark is an in-memory cluster-based parallel processing system that provides a wide range of functionalities such as graph processing, machine learning, stream processing, and SQL. This book aims to take your knowledge of Spark to the next level by teaching you how to expand Spark's functionality and implement your data flows and machine/deep learning programs on top of the platform. The book commences with an overview of the Spark ecosystem. It will introduce you to Project Tungsten and Catalyst, two of the major advancements of Apache Spark 2.x. You will understand how memory management and binary processing, cache-aware computation, and code generation are used to speed things up dramatically. The book extends to show how to incorporate H20, SystemML, and Deeplearning4j for machine learning, and Jupyter Notebooks and Kubernetes/Docker for cloud-based Spark. During the course of the book, you will learn about the latest enhancements to Apache Spark 2.x, such as interactive querying of live data and unifying DataFrames and Datasets. You will also learn about the updates on the APIs ...
    Note: Previous edition published: 2015. - Description based on online resource; title from title page (Safari, viewed August 14, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781786462749/?ar
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  • 3
    Online Resource
    Online Resource
    Apache Spark 2 data processing and real-time analytics : master complex big data processing, stream analytics, and machine learning with Apache (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789959918 , 1789959918
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Data mining ; Big data ; Machine learning ; Electronic data processing ; Electronic books ; Electronic books ; local
    Abstract: Build efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing framework Key Features Master the art of real-time big data processing and machine learning Explore a wide range of use-cases to analyze large data Discover ways to optimize your work by using many features of Spark 2.x and Scala Book Description Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. This Learning Path includes content from the following Packt products: Mastering Apache Spark 2.x by Romeo Kienzler Scala and Spark for Big Data Analytics by Md. Rezaul Karim, Sridhar Alla Apache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen MeiCookbook What you will learn Get to grips with all the features of Apache Spark 2.x Perform highly optimized real-time big data processing Use ML and DL techniques with Spark MLlib and third-party tools Analyze structured and unstructured data using SparkSQL and GraphX Understand tuning, debugging, and monitoring of big data applications Build scalable and fault-tolerant streaming applications Develop scalable recommendation engines Who this book is for If you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. Big data professionals who want to learn how to integrate and use the features of Apache Spark and build a strong big data pipeline will also find this Learning Path useful. To grasp the concepts explained in this Learning Path, you must know the fundamentals of Apache Spark and Scala.
    Note: Description based on online resource; title from title page (Safari, viewed March 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789959208/?ar
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