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You're reading from Mastering Machine Learning with Spark 2.x Harness the potential of machine learning, through spark

Product type Paperback

Published in Aug 2017

Publisher Packt

ISBN-13 9781785283451

Length 340 pages

Edition 1st Edition

Languages

Java

Tools

Apache Spark

Concepts

Machine Learning

Authors (3):

Alex Tellez

Michal Malohlava

Max Pumperla

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Table of Contents (9) Chapters

Preface

1. Introduction to Large-Scale Machine Learning and Spark

2. Detecting Dark Matter - The Higgs-Boson Particle FREE CHAPTER

3. Ensemble Methods for Multi-Class Classification

4. Predicting Movie Reviews Using NLP and Spark Streaming

5. Word2vec for Prediction and Clustering

6. Extracting Patterns from Clickstream Data

7. Graph Analytics with GraphX

8. Lending Club Loan Prediction

What you need for this book

Code samples provided in this book use Apache Spark 2.1 and its Scala API. Furthermore, we utilize the Sparkling Water package to access the H2O machine learning library. In each chapter, we show how to start Spark using spark-shell, and also how to download the data necessary to run the code.

In summary, the basic requirements to run the code provided in this book include:

Java 8
Spark 2.1

The rest of the chapter is locked

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Authors (3)

Max Pumperla

Max Pumperla is a data scientist and engineer specializing in deep learning and its applications. He currently works as a deep learning engineer at Skymind and is a co-founder of aetros.com. Max is the author and maintainer of several Python packages, including elephas, a distributed deep learning library using Spark. His open source footprint includes contributions to many popular machine learning libraries, such as keras, deeplearning4j, and hyperopt. He holds a PhD in algebraic geometry from the University of Hamburg.

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Tellez

Alex Tellez is a life-long data hacker/enthusiast with a passion for data science and its application to business problems. He has a wealth of experience working across multiple industries, including banking, health care, online dating, human resources, and online gaming. Alex has also given multiple talks at various AI/machine learning conferences, in addition to lectures at universities about neural networks. When hes not neck-deep in a textbook, Alex enjoys spending time with family, riding bikes, and utilizing machine learning to feed his French wine curiosity!

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Malohlava

Michal Malohlava, creator of Sparkling Water, is a geek and the developer; Java, Linux, programming languages enthusiast who has been developing software for over 10 years. He obtained his PhD from Charles University in Prague in 2012, and post doctorate from Purdue University. During his studies, he was interested in the construction of not only distributed but also embedded and real-time, component-based systems, using model-driven methods and domain-specific languages. He participated in the design and development of various systems, including SOFA and Fractal component systems and the jPapabench control system. Now, his main interest is big data computation. He participates in the development of the H2O platform for advanced big data math and computation, and its embedding into Spark engine, published as a project called Sparkling Water.

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