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Machine Learning with Spark
Machine Learning with Spark

Machine Learning with Spark: Develop intelligent, distributed machine learning systems , Second Edition

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Profile Icon Rajdeep Dua Profile Icon Manpreet Singh Ghotra Profile Icon Brian O'Neill Profile Icon Stephen Boesch Profile Icon Nick Pentreath +1 more Show less
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₹999.99 ₹3455.99
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3 (9 Ratings)
eBook Apr 2017 532 pages 2nd Edition
eBook
₹999.99 ₹3455.99
Paperback
₹4319.99
Subscription
Free Trial
Renews at ₹800p/m
Arrow left icon
Profile Icon Rajdeep Dua Profile Icon Manpreet Singh Ghotra Profile Icon Brian O'Neill Profile Icon Stephen Boesch Profile Icon Nick Pentreath +1 more Show less
Arrow right icon
₹999.99 ₹3455.99
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3 (9 Ratings)
eBook Apr 2017 532 pages 2nd Edition
eBook
₹999.99 ₹3455.99
Paperback
₹4319.99
Subscription
Free Trial
Renews at ₹800p/m
eBook
₹999.99 ₹3455.99
Paperback
₹4319.99
Subscription
Free Trial
Renews at ₹800p/m

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Machine Learning with Spark

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Key benefits

  • Get to the grips with the latest version of Apache Spark
  • Utilize Spark's machine learning library to implement predictive analytics
  • Leverage Spark’s powerful tools to load, analyze, clean, and transform your data

Description

This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML. Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML. By the end of this book, you will acquire the skills to leverage Spark's features to create your own scalable machine learning applications and power a modern data-driven business.

Who is this book for?

If you have a basic knowledge of machine learning and want to implement various machine-learning concepts in the context of Spark ML, this book is for you. You should be well versed with the Scala and Python languages.

What you will learn

  • * Get hands-on with the latest version of Spark ML
  • * Create your first Spark program with Scala and Python
  • * Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2
  • * Access public machine learning datasets and use Spark to load, process, clean, and transform data
  • * Use Spark s machine learning library to implement programs by utilizing well-known machine learning models
  • * Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models
  • * Write Spark functions to evaluate the performance of your machine learning models

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Apr 28, 2017
Length: 532 pages
Edition : 2nd
Language : English
ISBN-13 : 9781785886423
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Languages :

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Product Details

Publication date : Apr 28, 2017
Length: 532 pages
Edition : 2nd
Language : English
ISBN-13 : 9781785886423
Category :
Languages :

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Frequently bought together


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Apache Spark 2.x Machine Learning Cookbook
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Total 13,406.97 Stars icon

Table of Contents

12 Chapters
Getting Up and Running with Spark Chevron down icon Chevron up icon
Math for Machine Learning Chevron down icon Chevron up icon
Designing a Machine Learning System Chevron down icon Chevron up icon
Obtaining, Processing, and Preparing Data with Spark Chevron down icon Chevron up icon
Building a Recommendation Engine with Spark Chevron down icon Chevron up icon
Building a Classification Model with Spark Chevron down icon Chevron up icon
Building a Regression Model with Spark Chevron down icon Chevron up icon
Building a Clustering Model with Spark Chevron down icon Chevron up icon
Dimensionality Reduction with Spark Chevron down icon Chevron up icon
Advanced Text Processing with Spark Chevron down icon Chevron up icon
Real-Time Machine Learning with Spark Streaming Chevron down icon Chevron up icon
Pipeline APIs for Spark ML Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
(9 Ratings)
5 star 22.2%
4 star 22.2%
3 star 22.2%
2 star 0%
1 star 33.3%
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Top Reviews

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UJJAWAL SINHA Aug 15, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great Book! I recommend to buy it if you want to know practical guide on Machine Learning using spark 2.0 and scala .
Amazon Verified review Amazon
Amazon Customer Aug 07, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Perfect book for someone who is just starting his adventure with Spark and Machine Learning. The author has very didactic approach that guides the reader step by step from understanding first the basics, installing the environment, implementing and training models, evaluating, etc. I strongly recommend this book.
Amazon Verified review Amazon
PJG Mar 24, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
This book is a nice introduction to using the Apache Spark framework. It assumes no prior knowledge of either Hadoop, Spark or machine learning itself (although the latter is covered at quite a rapid pace in places so some background would likely be helpful!). The code examples are presented in Python and (mainly) Scala, with examples that are reasonably well-described.The overall tone of the book is clear and the chapters progress in a logical order, with a fairly rapid journey through the main machine learning techniques from a Spark perspective. Later chapters were particularly interesting, covering text mining and more complex methods (e.g. feature hashing).Some of the example data sets feel a little 'tired' (movie ratings data yet again - or perhaps I've just read too many machine learning books), but otherwise this is a good book and comes recommended.
Amazon Verified review Amazon
Ebot Tabi Aug 24, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
This book gives a great introduction to using the Apache Spark framework, a goto for anyone who wishes to learn how to use Apache Spark framework. It assumes no prior knowledge of either Hadoop or Spark. The code examples are presented in Python and Scala are well-described.The overall the book is clearly structured and the chapters progress in a logical order, with a fairly rapid introduction to machine learning techniques from a Spark perspective.I definitely do recommend this book for beginners.
Amazon Verified review Amazon
Mukesh Rao Apr 22, 2017
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
Did not find as useful as ML in R by Bret Lantz
Amazon Verified review Amazon
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