Skip to main content
  • Book
  • © 2020

Next-Generation Machine Learning with Spark

Covers XGBoost, LightGBM, Spark NLP, Distributed Deep Learning with Keras, and More

Apress

Authors:

  • For the latest version of Spark and Spark MLlib
  • Covers powerful third-party machine learning algorithms and libraries not available in the standard Spark MLlib library such as XGBoost4J-Spark, LightGBM on Spark, Isolation Forest, Spark NLP, and Stanford CoreNLP
  • Includes distributed deep learning using convolutional neural networks with Spark and Keras

Buy it now

Buying options

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

This is a preview of subscription content, log in via an institution to check for access.

Table of contents (7 chapters)

  1. Front Matter

    Pages i-xix
  2. Introduction to Machine Learning

    • Butch Quinto
    Pages 1-27
  3. Introduction to Spark and Spark MLlib

    • Butch Quinto
    Pages 29-96
  4. Supervised Learning

    • Butch Quinto
    Pages 97-187
  5. Unsupervised Learning

    • Butch Quinto
    Pages 189-244
  6. Recommendations

    • Butch Quinto
    Pages 245-268
  7. Graph Analysis

    • Butch Quinto
    Pages 269-287
  8. Deep Learning

    • Butch Quinto
    Pages 289-348
  9. Back Matter

    Pages 349-355

About this book

Access real-world documentation and examples for the Spark platform for building large-scale, enterprise-grade machine learning 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 algorithm 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 Analysis
  • Perform image recognition using convolutional neural networks
  • Utilize the Keras framework 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.


Authors and Affiliations

  • Carson, USA

    Butch Quinto

About the author

Butch Quinto is founder and Chief AI Officer at Intelvi AI, an artificial intelligence company that develops cutting-edge solutions for the defense, industrial, and transportation industries. As Chief AI Officer, Butch heads strategy, innovation, research, and development. Previously, he was the Director of Artificial Intelligence at a leading technology firm and Chief Data Officer at an AI startup. As Director of Analytics at Deloitte, Butch led the development of several enterprise-grade AI and IoT solutions as well as strategy, business development, and venture capital due diligence. He has more than 20 years of experience in various technology and leadership roles in several industries including banking and finance, telecommunications, government, utilities, transportation, e-commerce, retail, manufacturing, and bioinformatics. Butch is the author of Next-Generation Big Data (Apress) and a member of the Association for the Advancement of Artificial Intelligence andthe American Association for the Advancement of Science. 

Bibliographic Information

  • Book Title: Next-Generation Machine Learning with Spark

  • Book Subtitle: Covers XGBoost, LightGBM, Spark NLP, Distributed Deep Learning with Keras, and More

  • Authors: Butch Quinto

  • DOI: https://doi.org/10.1007/978-1-4842-5669-5

  • Publisher: Apress Berkeley, CA

  • eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)

  • Copyright Information: Butch Quinto 2020

  • Softcover ISBN: 978-1-4842-5668-8Published: 23 February 2020

  • eBook ISBN: 978-1-4842-5669-5Published: 22 February 2020

  • Edition Number: 1

  • Number of Pages: XIX, 355

  • Number of Illustrations: 67 b/w illustrations

  • Topics: Big Data

Buy it now

Buying options

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access