Deep Learning with R (Hardcover, 1st ed. 2019)

Abhijit Ghatak

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Deep Learning with R introduces deep learning and neural networks using the R programming language. The book builds on the understanding of the theoretical and mathematical constructs and enables the reader to create applications on computer vision, natural language processing and transfer learning. The book starts with an introduction to machine learning and moves on to describe the basic architecture, different activation functions, forward propagation, cross-entropy loss and backward propagation of a simple neural network. It goes on to create different code segments to construct deep neural networks. It discusses in detail the initialization of network parameters, optimization techniques, and some of the common issues surrounding neural networks such as dealing with NaNs and the vanishing/exploding gradient problem. Advanced variants of multilayered perceptrons namely, convolutional neural networks and sequence models are explained, followed by application to different use cases. The book makes extensive use of the Keras and TensorFlow frameworks.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Release date:	April 2019
First published:	2019
Authors:	Abhijit Ghatak
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	245
Edition:	1st ed. 2019
ISBN-13:	978-981-13-5849-4
Categories:	Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Computing & IT > Computer programming > General Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	981-13-5849-4
Barcode:	9789811358494