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Deep Learning with R

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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28 Şubat 2018 21,6 x 0,6 x 27,9 cm Kolektif 15 x 0,5 x 22 cm 15 x 0,7 x 22 cm 15 x 0,3 x 22 cm 8 Haziran 2020 Flower Love Press 1 Ocak 2017 1 Ocak 2016 Collectif BrownTrout Publisher 15 x 0,4 x 22 cm 1 Haziran 2018 U.S. Department of the Interior Dazzle Book Press 1 Ocak 2018 15 x 0,6 x 22 cm
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Sürüm ayrıntıları
yazar Abhijit Ghatak
isbn 10 9811370893
isbn 13 978-9811370892
Yayımcı Springer; 2019 ed.. baskı
Dilim İngilizce
Boyutlar ve boyutlar 15,5 x 1,6 x 23,5 cm
Tarafından yayınlandı Deep Learning with R 8 Haziran 2020

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