Introduction to deep learning using R : a step-by-step guide to learning and implementing deep learning models using R / Taweh Beysolow II.
Material type: TextSeries: 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
- unmediated
- volume
- 9781484227336
- 006.31 BEY 23
- Q325.5 .B49 2017
Item type | Current library | Collection | Call number | Status | Date due | Barcode |
---|---|---|---|---|---|---|
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.
There are no comments on this title.