Book Image

Deep Learning with TensorFlow and Keras – 3rd edition - Third Edition

By : Amita Kapoor, Antonio Gulli, Sujit Pal
5 (2)
Book Image

Deep Learning with TensorFlow and Keras – 3rd edition - Third Edition

5 (2)
By: Amita Kapoor, Antonio Gulli, Sujit Pal

Overview of this book

Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow 2.x focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs based on Keras, and flexible model building on any platform. This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical examples for the cloud, mobile, and large production environments. This book also shows you how to create neural networks with TensorFlow, runs through popular algorithms (regression, convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), recurrent neural networks (RNNs), natural language processing (NLP), and graph neural networks (GNNs)), covers working example apps, and then dives into TF in production, TF mobile, and TensorFlow with AutoML.
Table of Contents (23 chapters)
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Neural Network Foundations with TF

In this chapter, we learn the basics of TensorFlow, an open-source library developed by Google for machine learning and deep learning. In addition, we introduce the basics of neural networks and deep learning, two areas of machine learning that have had incredible Cambrian growth during the last few years. The idea behind this chapter is to provide all the tools needed to do basic but fully hands-on deep learning.

We will learn:

  • What TensorFlow and Keras are
  • An introduction to neural networks
  • What the perceptron and multi-layer perceptron are
  • A real example: recognizing handwritten digits

All the code files for this chapter can be found at

Let’s begin!