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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
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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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Image classification using the MXNet library

The MXNet package was introduced in Chapter 1, Getting Started with Deep Learning, so go back to that chapter for instructions on how to install the package if you have not already done so. We will demonstrate how to get almost 100% accuracy on a classification task for image data. We will use the MNIST dataset that we introduced in Chapter 2, Image Classification Using Convolutional Neural Networks. This dataset contains images of handwritten digits (0-9), and all images are of size 28 x 28. It is the Hello World! equivalent in deep learning. There’s a long-term competition on Kaggle that uses this dataset. The script Chapter5/explore.Rmd is an R markdown file that explores this dataset.

  1. First, we will check if the data has already been downloaded, and if it has not, we will download it. If the data is not available at this...
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R Deep Learning Essentials. - Second Edition
Published in: Aug 2018Publisher: PacktISBN-13: 9781788992893

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