What this book covers
Chapter 1, Getting Started with Deep Learning, covers the concepts that will be found in all the subsequent chapters. The basics of machine learning and deep learning are also discussed. We will also look at Deep learning architectures that are distinguished from the more commonplace single-hidden-layer neural networks by their depth, that is, the number of node layers through which data passes in a multistep process of pattern recognition. We will also analyze these architectures with a chart summarizing all the neural networks from where most of the deep learning algorithm evolved. The chapter ends with an analysis of the major deep learning frameworks.
Chapter 2, A First Look at TensorFlow, gives a detailed description ...
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