Book Image

Deep Learning with TensorFlow 2 and Keras - Second Edition

By : Antonio Gulli, Amita Kapoor, Sujit Pal
Book Image

Deep Learning with TensorFlow 2 and Keras - Second Edition

By: Antonio Gulli, Amita Kapoor, Sujit Pal

Overview of this book

Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside 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 is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2 provides full Keras integration, making advanced machine learning easier and more convenient than ever before. This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML.
Table of Contents (19 chapters)
17
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18
Index

TensorFlow and Cloud

AI algorithms require extensive computing resources. With the availability of a large number of cloud platforms offering their services at competitive prices, cloud computing offers a cost-effective solution. In this chapter, we will talk about three main cloud platform providers that occupy the majority of the market share: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform. Moreover, once you have trained your model on cloud, you can use TensorFlow Extended (TFX) to move your model to production. The chapter will cover:

  • Creating and using virtual machines on cloud
  • Creating and training directly on Jupyter Notebook on cloud
  • Deploying the model on cloud
  • Using TFX for production
  • TensorFlow Enterprise