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You're reading from  R Deep Learning Essentials. - Second Edition

Product typeBook
Published inAug 2018
Reading LevelIntermediate
PublisherPackt
ISBN-139781788992893
Edition2nd Edition
Languages
R
Tools
H2O
Concepts
Deep Learning
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Authors (2):
Mark Hodnett
Mark Hodnett
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Mark Hodnett

Mark Hodnett is a data scientist with over 20 years of industry experience in software development, business intelligence systems, and data science. He has worked in a variety of industries, including CRM systems, retail loyalty, IoT systems, and accountancy. He holds a master's in data science and an MBA. He works in Cork, Ireland, as a senior data scientist with AltViz.
Read more about Mark Hodnett

Joshua F. Wiley
Joshua F. Wiley
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Joshua F. Wiley

Joshua F. Wiley is a lecturer at Monash University, conducting quantitative research on sleep, stress, and health. He earned his Ph.D. from the University of California, Los Angeles and completed postdoctoral training in primary care and prevention. In statistics and data science, Joshua focuses on biostatistics and is interested in reproducible research and graphical displays of data and statistical models. He develops or co-develops a number of R packages including Varian, a package to conduct Bayesian scale-location structural equation models, and MplusAutomation, a popular package that links R to the commercial Mplus software.
Read more about Joshua F. Wiley

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Use case – using MXNet for classification and regression

In this section, we will use a new dataset to create a binary classification task. The dataset we will use here is a transactional dataset that is available at https://www.dunnhumby.com/sourcefiles. This dataset has been made available from dunnhumby, which is perhaps best known for its link to the Tesco (a British grocery store) club-card, which is one of the largest retail loyalty systems in the world. I recommend the following book, which describes how dunnhumby helped Tesco to become the number one retailer by applying analytics to their retail loyalty program: Humby, Clive, Terry Hunt, and Tim Phillips. Scoring points. Kogan Page Publishers, 2008. Even though this book is relatively old, it remains one of the best use cases to describe how to roll out a business-transformation program based on data analytics...

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R Deep Learning Essentials. - Second Edition
Published in: Aug 2018Publisher: PacktISBN-13: 9781788992893
© 2018 Packt Publishing Limited All Rights Reserved

Authors (2)

author image
Mark Hodnett

Mark Hodnett is a data scientist with over 20 years of industry experience in software development, business intelligence systems, and data science. He has worked in a variety of industries, including CRM systems, retail loyalty, IoT systems, and accountancy. He holds a master's in data science and an MBA. He works in Cork, Ireland, as a senior data scientist with AltViz.
Read more about Mark Hodnett

author image
Joshua F. Wiley

Joshua F. Wiley is a lecturer at Monash University, conducting quantitative research on sleep, stress, and health. He earned his Ph.D. from the University of California, Los Angeles and completed postdoctoral training in primary care and prevention. In statistics and data science, Joshua focuses on biostatistics and is interested in reproducible research and graphical displays of data and statistical models. He develops or co-develops a number of R packages including Varian, a package to conduct Bayesian scale-location structural equation models, and MplusAutomation, a popular package that links R to the commercial Mplus software.
Read more about Joshua F. Wiley

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