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Apache Spark 2.x Machine Learning Cookbook
Apache Spark 2.x Machine Learning Cookbook

Apache Spark 2.x Machine Learning Cookbook: Over 100 recipes to simplify machine learning model implementations with Spark

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Profile Icon Mohammed Guller Profile Icon Amirghodsi Profile Icon Rajendran Profile Icon Hall Profile Icon Shuen Mei +1 more Show less
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Can$12.99 Can$55.99
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3 (2 Ratings)
eBook Sep 2017 666 pages 1st Edition
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Can$12.99 Can$55.99
Paperback
Can$69.99
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Arrow left icon
Profile Icon Mohammed Guller Profile Icon Amirghodsi Profile Icon Rajendran Profile Icon Hall Profile Icon Shuen Mei +1 more Show less
Arrow right icon
Can$12.99 Can$55.99
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3 (2 Ratings)
eBook Sep 2017 666 pages 1st Edition
eBook
Can$12.99 Can$55.99
Paperback
Can$69.99
Subscription
Free Trial
eBook
Can$12.99 Can$55.99
Paperback
Can$69.99
Subscription
Free Trial

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Apache Spark 2.x Machine Learning Cookbook

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Key benefits

  • Solve the day-to-day problems of data science with Spark
  • This unique cookbook consists of exciting and intuitive numerical recipes
  • Optimize your work by acquiring, cleaning, analyzing, predicting, and visualizing your data

Description

Machine learning aims to extract knowledge from data, relying on fundamental concepts in computer science, statistics, probability, and optimization. Learning about algorithms enables a wide range of applications, from everyday tasks such as product recommendations and spam filtering to cutting edge applications such as self-driving cars and personalized medicine. You will gain hands-on experience of applying these principles using Apache Spark, a resilient cluster computing system well suited for large-scale machine learning tasks. This book begins with a quick overview of setting up the necessary IDEs to facilitate the execution of code examples that will be covered in various chapters. It also highlights some key issues developers face while working with machine learning algorithms on the Spark platform. We progress by uncovering the various Spark APIs and the implementation of ML algorithms with developing classification systems, recommendation engines, text analytics, clustering, and learning systems. Toward the final chapters, we’ll focus on building high-end applications and explain various unsupervised methodologies and challenges to tackle when implementing with big data ML systems.

Who is this book for?

This book is for Scala developers with a fairly good exposure to and understanding of machine learning techniques, but lack practical implementations with Spark. A solid knowledge of machine learning algorithms is assumed, as well as hands-on experience of implementing ML algorithms with Scala. However, you do not need to be acquainted with the Spark ML libraries and ecosystem.

What you will learn

  • Get to know how Scala and Spark go hand-in-hand for developers when developing ML systems with Spark
  • Build a recommendation engine that scales with Spark
  • Find out how to build unsupervised clustering systems to classify data in Spark
  • Build machine learning systems with the Decision Tree and Ensemble models in Spark
  • Deal with the curse of high-dimensionality in big data using Spark
  • Implement Text analytics for Search Engines in Spark
  • Streaming Machine Learning System implementation using Spark

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Sep 22, 2017
Length: 666 pages
Edition : 1st
Language : English
ISBN-13 : 9781782174608
Vendor :
Apache
Category :
Languages :

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Product Details

Publication date : Sep 22, 2017
Length: 666 pages
Edition : 1st
Language : English
ISBN-13 : 9781782174608
Vendor :
Apache
Category :
Languages :

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Frequently bought together


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Apache Spark 2.x Machine Learning Cookbook
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Table of Contents

13 Chapters
Practical Machine Learning with Spark Using Scala Chevron down icon Chevron up icon
Just Enough Linear Algebra for Machine Learning with Spark Chevron down icon Chevron up icon
Spark's Three Data Musketeers for Machine Learning - Perfect Together Chevron down icon Chevron up icon
Common Recipes for Implementing a Robust Machine Learning System Chevron down icon Chevron up icon
Practical Machine Learning with Regression and Classification in Spark 2.0 - Part I Chevron down icon Chevron up icon
Practical Machine Learning with Regression and Classification in Spark 2.0 - Part II Chevron down icon Chevron up icon
Recommendation Engine that Scales with Spark Chevron down icon Chevron up icon
Unsupervised Clustering with Apache Spark 2.0 Chevron down icon Chevron up icon
Optimization - Going Down the Hill with Gradient Descent Chevron down icon Chevron up icon
Building Machine Learning Systems with Decision Tree and Ensemble Models Chevron down icon Chevron up icon
Curse of High-Dimensionality in Big Data Chevron down icon Chevron up icon
Implementing Text Analytics with Spark 2.0 ML Library Chevron down icon Chevron up icon
Spark Streaming and Machine Learning Library Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
(2 Ratings)
5 star 50%
4 star 0%
3 star 0%
2 star 0%
1 star 50%
JIMMY WANG Nov 18, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great book! Very thorough with lots of examples. Will come back with more thoughts after finishing the whole book.
Amazon Verified review Amazon
taiwo Raphael Alabi Dec 06, 2018
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
Terrible book! DO not buy!
Amazon Verified review Amazon
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