Next-Generation Machine Learning with Spark

Next-Generation Machine Learning with Spark Front Cover
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2020-03-24
355 pages

Book Description

Access real-world documentation and examples for the Spark platform for building large-scale, -grade applications.

The past decade has seen an astonishing series of advances in machine learning. These breakthroughs are disrupting our everyday life and making an impact across every industry.

Next-Generation Machine Learning with Spark provides a gentle introduction to Spark and Spark MLlib and advances to more powerful, third-party machine learning algorithms and libraries beyond what is available in the standard Spark MLlib library. By the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations. 

What You Will Learn

  • Be introduced to machine learning, Spark, and Spark MLlib 2.4.x
  • Achieve lightning-fast gradient boosting on Spark with the XGBoost4J-Spark and LightGBM libraries
  • Detect anomalies with the Isolation Forest for Spark
  • Use the Spark NLP and Stanford CoreNLP libraries that support multiple languages
  • Optimize your ML workload with the Alluxio in-memory data accelerator for Spark
  • Use GraphX and GraphFrames for Graph
  • Perform image recognition using convolutional neural
  • Utilize the Keras and distributed deep learning libraries with Spark 

Who This Book Is For

Data scientists and machine learning engineers who want to take their knowledge to the next level and use Spark and more powerful, next-generation algorithms and libraries beyond what is available in the standard Spark MLlib library; also serves as a primer for aspiring data scientists and engineers who need an introduction to machine learning, Spark, and Spark MLlib.

Book Details

  • Title: Next-Generation Machine Learning with Spark
  • Author:
  • Length: 355 pages
  • Edition: 1st ed.
  • Language: English
  • Publisher:
  • Publication Date: 2020-03-24
  • ISBN-10: 1484256689
  • ISBN-13: 9781484256688
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