Tellez - Mastering Machine Learning with Spark 2.x

BIRMINGHAM - MUMBAI

Copyright 2017 Packt Publishing

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First published: August 2017

Production reference: 1290817

ISBN 978-1-78528-345-1

www.packtpub.com

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!

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.

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.

Dipanjan Deb is an experienced analytic professional with over 17 years of cumulative experience in machine/statistical learning, data mining and predictive analytics across finance, healthcare, automotive, CPG, automotive, energy, and human resource domains. He is highly proficient in developing cutting-edge analytic solutions using open source and commercial software to integrate multiple systems in order to provide massively parallelized and large-scale optimization.

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Big data that was our motivation to explore the world of machine learning with Spark a couple of years ago. We wanted to build machine learning applications that would leverag models trained on large amounts of data, but the beginning was not easy. Spark was still evolving, it did not contain a powerful machine learning library, and we were still trying to figure out what it means to build a machine learning application.