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Mastering Machine Learning with Spark 2.x
Mastering Machine Learning with Spark 2.x

Mastering Machine Learning with Spark 2.x: Harness the potential of machine learning, through spark

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Profile Icon Malohlava Profile Icon Tellez Profile Icon Max Pumperla
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$38.99 $43.99
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
eBook Aug 2017 340 pages 1st Edition
eBook
$38.99 $43.99
Paperback
$54.99
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Free Trial
Renews at $19.99p/m
Arrow left icon
Profile Icon Malohlava Profile Icon Tellez Profile Icon Max Pumperla
Arrow right icon
$38.99 $43.99
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
eBook Aug 2017 340 pages 1st Edition
eBook
$38.99 $43.99
Paperback
$54.99
Subscription
Free Trial
Renews at $19.99p/m
eBook
$38.99 $43.99
Paperback
$54.99
Subscription
Free Trial
Renews at $19.99p/m

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Mastering Machine Learning with Spark 2.x

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Key benefits

  • • Process and analyze big data in a distributed and scalable way
  • • Write sophisticated Spark pipelines that incorporate elaborate extraction
  • • Build and use regression models to predict flight delays

Description

The purpose of machine learning is to build systems that learn from data. Being able to understand trends and patterns in complex data is critical to success; it is one of the key strategies to unlock growth in the challenging contemporary marketplace today. With the meteoric rise of machine learning, developers are now keen on finding out how can they make their Spark applications smarter. This book gives you access to transform data into actionable knowledge. The book commences by defining machine learning primitives by the MLlib and H2O libraries. You will learn how to use Binary classification to detect the Higgs Boson particle in the huge amount of data produced by CERN particle collider and classify daily health activities using ensemble Methods for Multi-Class Classification. Next, you will solve a typical regression problem involving flight delay predictions and write sophisticated Spark pipelines. You will analyze Twitter data with help of the doc2vec algorithm and K-means clustering. Finally, you will build different pattern mining models using MLlib, perform complex manipulation of DataFrames using Spark and Spark SQL, and deploy your app in a Spark streaming environment.

Who is this book for?

Are you a developer with a background in machine learning and statistics who is feeling limited by the current slow and “small data” machine learning tools? Then this is the book for you! In this book, you will create scalable machine learning applications to power a modern data-driven business using Spark. We assume that you already know the machine learning concepts and algorithms and have Spark up and running (whether on a cluster or locally) and have a basic knowledge of the various libraries contained in Spark.

What you will learn

  • • Use Spark streams to cluster tweets online
  • • Run the PageRank algorithm to compute user influence
  • • Perform complex manipulation of DataFrames using Spark
  • • Define Spark pipelines to compose individual data transformations
  • • Utilize generated models for off-line/on-line prediction
  • • Transfer the learning from an ensemble to a simpler Neural Network
  • • Understand basic graph properties and important graph operations
  • • Use GraphFrames, an extension of DataFrames to graphs, to study graphs using an elegant query language
  • • Use K-means algorithm to cluster movie reviews dataset

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Aug 31, 2017
Length: 340 pages
Edition : 1st
Language : English
ISBN-13 : 9781785282416
Vendor :
Apache
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What do you get with eBook?

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Product Details

Publication date : Aug 31, 2017
Length: 340 pages
Edition : 1st
Language : English
ISBN-13 : 9781785282416
Vendor :
Apache
Category :
Languages :

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Frequently bought together


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Total $ 170.97
Mastering Spark for Data Science
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Mastering Machine Learning with Spark 2.x
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Apache Spark 2.x Machine Learning Cookbook
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Total $ 170.97 Stars icon

Table of Contents

8 Chapters
Introduction to Large-Scale Machine Learning and Spark Chevron down icon Chevron up icon
Detecting Dark Matter - The Higgs-Boson Particle Chevron down icon Chevron up icon
Ensemble Methods for Multi-Class Classification Chevron down icon Chevron up icon
Predicting Movie Reviews Using NLP and Spark Streaming Chevron down icon Chevron up icon
Word2vec for Prediction and Clustering Chevron down icon Chevron up icon
Extracting Patterns from Clickstream Data Chevron down icon Chevron up icon
Graph Analytics with GraphX Chevron down icon Chevron up icon
Lending Club Loan Prediction Chevron down icon Chevron up icon

Customer reviews

Rating distribution
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(1 Ratings)
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Canming Oct 21, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Awesome book to get you started in machine learning.
Amazon Verified review Amazon
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