Introducing Advanced Deep Learning with Keras

In this first chapter, we will introduce three deep learning artificial neural networks that we will be using throughout the book. These networks are MLP, CNN, and RNN (defined and described in Section 2), which are the building blocks of selected advanced deep learning topics covered in this book, such as autoregressive networks (autoencoder, GAN, and VAE), deep reinforcement learning, object detection and segmentation, and unsupervised learning using mutual information.

Together, we'll discuss how to implement MLP, CNN, and RNN based models using the Keras library in this chapter. More specifically, we will use the TensorFlow Keras library called tf.keras. We'll start by looking at why tf.keras ...

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