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The Resource R Deep learning essentials : build automatic classification and prediction models using unsupervised learning, Joshua F. Wiley

R Deep learning essentials : build automatic classification and prediction models using unsupervised learning, Joshua F. Wiley

Label
R Deep learning essentials : build automatic classification and prediction models using unsupervised learning
Title
R Deep learning essentials
Title remainder
build automatic classification and prediction models using unsupervised learning
Statement of responsibility
Joshua F. Wiley
Creator
Author
Subject
Language
eng
Summary
Annotation
Member of
Cataloging source
UMI
http://library.link/vocab/creatorName
Wiley, Joshua F
Dewey number
006.31
Illustrations
illustrations
Index
index present
LC call number
Q325.5
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
Community experience distilled
http://library.link/vocab/subjectName
  • Machine learning
  • R (Computer program language)
  • Data mining
  • COMPUTERS
  • Data mining
  • Machine learning
  • R (Computer program language)
Summary expansion
Build automatic classification and prediction models using unsupervised learningAbout This Book Harness the ability to build algorithms for unsupervised data using deep learning concepts with R Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models Build models relating to neural networks, prediction and deep predictionWho This Book Is ForThis book caters to aspiring data scientists who are well versed with machine learning concepts with R and are looking to explore the deep learning paradigm using the packages available in R. You should have a fundamental understanding of the R language and be comfortable with statistical algorithms and machine learning techniques, but you do not need to be well versed with deep learning concepts.What You Will Learn Set up the R package H2O to train deep learning models Understand the core concepts behind deep learning models Use Autoencoders to identify anomalous data or outliers Predict or classify data automatically using deep neural networks Build generalizable models using regularization to avoid overfitting the training dataIn DetailDeep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using model architectures. With the superb memory management and the full integration with multi-node big data platforms, the H2O engine has become more and more popular among data scientists in the field of deep learning.This book will introduce you to the deep learning package H2O with R and help you understand the concepts of deep learning. We will start by setting up important deep learning packages available in R and then move towards building models related to neural networks, prediction, and deep prediction, all of this with the help of real-life examples.After installing the H2O package, you will learn about prediction algorithms. Moving ahead, concepts such as overfitting data, anomalous data, and deep prediction models are explained. Finally, the book will cover concepts relating to tuning and optimizing models.Style and approachThis book takes a practical approach to showing you the concepts of deep learning with the R programming language. We will start with setting up important deep learning packages available in R and then move towards building models related to neural network, prediction, and deep prediction - and all of this with the help of real-life examples
Label
R Deep learning essentials : build automatic classification and prediction models using unsupervised learning, Joshua F. Wiley
Instantiates
Publication
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Control code
946526709
Dimensions
unknown
Extent
1 online resource
Form of item
online
Isbn
9781785284717
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations.
http://library.link/vocab/ext/overdrive/overdriveId
cl0500000732
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)946526709
Label
R Deep learning essentials : build automatic classification and prediction models using unsupervised learning, Joshua F. Wiley
Publication
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Control code
946526709
Dimensions
unknown
Extent
1 online resource
Form of item
online
Isbn
9781785284717
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations.
http://library.link/vocab/ext/overdrive/overdriveId
cl0500000732
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)946526709

Library Locations

    • Ellis LibraryBorrow it
      1020 Lowry Street, Columbia, MO, 65201, US
      38.944491 -92.326012
    • Engineering Library & Technology CommonsBorrow it
      W2001 Lafferre Hall, Columbia, MO, 65211, US
      38.946102 -92.330125
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