|Advanced Deep Learning with TensorFlow 2 and Keras 2nd Ed (Packt)|
|Monday, 29 June 2020|
This is a completely updated edition of a guide to the advanced deep learning techniques, revised for TensorFlow 2.x. In this edition author Rowel Atienza introduces the practical side of deep learning with new chapters on unsupervised learning using mutual information, object detection (SSD), and semantic segmentation (FCN and PSPNet). Using Keras as an open-source deep learning library, the book features hands-on projects. Starting with an overview of multi-layer perceptrons (MLPs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs), the book then introduces deep neural network architectures, including ResNet and DenseNet, and how to create autoencoders.
Author: Rowel Atienza
In his review of the 1st edition, Mike James awarded a rating of 4.5 out of 5 to this book which presents advanced examples and is strong on GANs.
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