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Chapter 8: Deep Learning

Chapter 8: Deep Learning

pp. 252-322

Authors

, Idaho State University
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Extract

Based on Chapter 6, in this chapter we expand the discussion of neural networks to include networks that have more than one hidden layer. Common structures such as the convolutional neural network (CNN) or the Long Short-Term Memory network (LSTM) are explained and used along with Matlab’s Deep Network Designer App as well as Matlab script to implement and train such networks. Issues such as the vanishing or exploding gradient, normalization, and training strategies are discussed. Concepts that address overfitting and the vanishing or exploding gradient are introduced, including dropout and regularization. Transfer learning is discussed and showcased using Matlab’s DND App.

Keywords

  • Deep learning
  • transfer learning
  • vanishing gradient
  • regularization
  • dropout
  • convolution
  • pooling
  • CNN
  • LSTM
  • Data augmentation
  • batch normalization

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