Scala and Spark for Big Data Analytics: Explore the concepts of functional programming, data streaming, and machine learning
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Scala and Spark for Big Data Analytics: Explore the concepts of functional programming, data streaming, and machine learning
By the end of this book, you will have a thorough understanding of Spark, and you will be able to perform full-stack data analytics with a feel that no amount of data is too big.
Scala and Spark for Big Data Analytics: Explore the concepts of functional programming, data streaming, and machine learning
товар №: 17438593

Scala and Spark for Big Data Analytics: Explore the concepts of functional programming, data streaming, and machine learning

67% of respondents would recommend this to a friend

товар №: 17438593

TJS 643

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By the end of this book, you will have a thorough understanding of Spark, and you will be able to perform full-stack data analytics with a feel that no amount of data is too big.
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What Stands Out

Functional Programming
Leverage Scala's functional programming paradigm to write cleaner, more maintainable code, enhancing productivity and making it easier to work with complex data transformations in big data analytics.
Data Streaming
Utilize Apache Spark's structured streaming capabilities to process real-time data efficiently, allowing businesses to react instantly to changing data sets, thereby gaining a competitive edge in analytics.
Machine Learning Integration
Combine Scala and Spark's powerful machine learning libraries to develop predictive models directly on big data, simplifying workflows and increasing accuracy for data-driven decision-making.

Информация о продукте

Learn functional programming, data streaming, and machine learning with Scala and Spark. Explore a wide range of big data analytics concepts. Shop now at Ubuy Tajikistan.
Publisher Packt Publishing
Publication date July 25, 2017
Language English
Print length 786 pages
ISBN-10 1785280848
ISBN-13 978-1785280849
Item Weight 2.92 pounds (1.32 kg)
Dimensions 7.5 x 1.8 x 9.25 inches (19.1 x 4.6 x 23.5 cm)

Who Should Buy?

Suitable For
  • Data Scientists

    Ideal for data scientists looking to integrate big data techniques with functional programming and machine learning.

  • Software Developers

    Great for developers aiming to enhance their skills in Scala and Apache Spark for big data projects.

  • Big Data Analysts

    Perfect for analysts seeking to learn data streaming and analytics for real-time processing with Scala and Spark.

Not Suitable For
  • Beginners

    Not suitable for those with little to no programming experience, as it requires a foundational understanding of concepts.

ОПИСАНИЕ ТОВАРА

Scala and Spark for Big Data Analytics: Explore the concepts of functional programming, data streaming, and machine learning

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Data Processing Editorial Review

Scala and Spark for Big Data Analytics provides a comprehensive exploration of functional programming, data streaming, and machine learning, perfect for anyone interested in using Scala with Spark. The book covers essential topics intricately, including numerous coding examples and challenges related to big data analytics. Users have noted that while the book is extensive with 786 pages, it serves as both a practical guide and a theoretical reference, making it suitable for both beginners and professionals transitioning from Java to Scala for big data processing. Its detailed description of various machine learning algorithms and advanced Spark topics is especially appreciated, providing a solid foundation for those seeking to enhance their big data skills.

Customer Reviews & Ratings

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Плюсы

  • In-depth explanations of complex concepts
  • Numerous practical examples for clarity
  • Covers a wide range of Spark operations
  • Useful guide for transitioning from Java to Scala
  • Includes real-life big data analytics problems

Минусы

  • Some code examples may require additional research

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Особенности и преимущества

  • Learn Scala's sophisticated type system combining functional programming and object-oriented concepts
  • Work on a wide array of applications, from simple batch jobs to stream processing and machine learning
  • Explore common and complex use-cases for large-scale data analysis with Spark
  • Develop Spark applications using SparkR and PySpark APIs
  • Understand machine-learning best practices and build predictive models with widely used algorithms in Spark MLlib & ML
  • Learn tuning, debugging, and monitoring Spark applications, and deploy them on real clusters in Standalone, Mesos, and YARN

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