Deep Learning Beyond the Basics

In this chapter, we will introduce deep models, and we will show three examples of how to build deep models. More specifically, in this chapter, you'll learn the following:

  • The basics of deep learning
  • How to optimize a deep net
  • The speed/complexity/accuracy problem
  • How to classify images with a CNN
  • How to use a pre-trained network for classification and transfer learning
  • How to operate on sequences using a LSTM

We will be using the Keras package (https://keras.io/), which is a high-level API for deep learning that will render approaching neural networks for deep learning much easier and more understandable because it is characterized by a Lego-like approach (here, the bricks are a neural network's composing ...

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