Deep Learning with R
Buch in deiner Nähe kaufen
Beschreibung
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.
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.
Offers a hands on approach to deep learning while explaining the theory and mathematical concepts in an intuitive manner Broadens the understanding of advanced neural networks including ConvNets and Sequence models Covers deep learning frameworks
Autor*in
Abhijit Ghatak
Themen in »Deep Learning with R«
Statistics Deep neural networks Regularization and hyper-parameter tuning Convolutional neural networks and sequence models
Stimmen zu »Deep Learning with R«
“This is a very useful book in the domain of deep learning and the author has done a great job of bringing all the paradigms and libraries together to illustrate how they work for real big data. I am glad to have this book on my shelf.” (Anna Bartkowiak, ISCB News, Vol. 68, December, 2019)
()