August 2016
Intermediate to advanced
420 pages
9h 35m
English
Between this and the previous chapter, we have come quite a long way covering the most important topics in deep learning. We now understand how to construct architectures by stacking multiple layers in a neural network and how to discern and utilize backpropagation methods. We also covered the concept of unsupervised pretraining with stacked and denoising autoencoders. The next and really exciting step in deep learning is the rapidly evolving field of Convolutional Neural Networks (CNN), a method of building multilayered, locally connected networks. CNNs, commonly referred to as ConvNets, are so rapidly evolving at the time of writing this book that we literally had to rewrite and update ...
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