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  3. Matematik til informatikfag

Deep Learning with R

Af: Abhijit Ghatak Engelsk Hardback

Deep Learning with R

Af: Abhijit Ghatak Engelsk Hardback
Tjek vores konkurrenters priser

 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. 


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Tjek vores konkurrenters priser
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kr 811
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Tjek vores konkurrenters priser

 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. 


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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 245
ISBN-13: 9789811358494
Indbinding: Hardback
Udgave:
ISBN-10: 9811358494
Kategori: Matematik til informatikfag
Udg. Dato: 26 apr 2019
Længde: 0mm
Bredde: 155mm
Højde: 235mm
Forlag: Springer Verlag, Singapore
Oplagsdato: 26 apr 2019
Forfatter(e): Abhijit Ghatak
Forfatter(e) Abhijit Ghatak

Kategori Matematik til informatikfag

ISBN-13 9789811358494

Sprog Engelsk

Indbinding Hardback

Sider 245

Udgave

Længde 0mm

Bredde 155mm

Højde 235mm

Udg. Dato 26 apr 2019

Oplagsdato 26 apr 2019

Forlag Springer Verlag, Singapore

Kategori sammenhænge