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Introduction to deep learning using R : a step-by-step guide to learning and implementing deep learning models using R / Taweh Beysolow II.

By: Material type: TextTextSeries: Books for professionals by professionalsPublisher: [Berkeley, California?] : Apress, [2017]Distributor: New York, NY : Distributed by Springer Science + Business Media Copyright date: ©2017Description: xix, 227 pages : illustrations ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781484227336
Subject(s): DDC classification:
  • 006.31 BEY 23
LOC classification:
  • Q325.5 .B49 2017
Contents:
Introduction to deep learning -- Mathematical review -- A review of optimization and machine learning -- Single and multilayer perceptron models -- Convolutional neural networks (CNNs) -- Recurrent neural networks (RNNs) -- Autoencoders, restricted boltzmann machines, and deep belief networks -- Experimental design and heuristics -- Hardware and software suggestions -- Machine learning example problems -- Deep learning and other example problems -- Closing statements.
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Holdings
Item type Current library Collection Call number Status Date due Barcode
Book Book Air University's Aerospace and Aviation Campus Kamra Computer Science Computer Science 006.31 BEY (Browse shelf(Opens below)) Available AUKP1179

Includes index.

Introduction to deep learning -- Mathematical review -- A review of optimization and machine learning -- Single and multilayer perceptron models -- Convolutional neural networks (CNNs) -- Recurrent neural networks (RNNs) -- Autoencoders, restricted boltzmann machines, and deep belief networks -- Experimental design and heuristics -- Hardware and software suggestions -- Machine learning example problems -- Deep learning and other example problems -- Closing statements.

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