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Deep Learning with TensorFlow 2 and Keras - Second Edition

You're reading from Deep Learning with TensorFlow 2 and Keras - Second Edition

Product type Book

Published in Dec 2019

Publisher Packt

ISBN-13 9781838823412

Pages 646 pages

Edition 2nd Edition

Languages

Concepts

Authors (3):

Antonio Gulli

Amita Kapoor

Sujit Pal

View More author details

Table of Contents (19) Chapters

Preface

1. Neural Network Foundations with TensorFlow 2.0

2. TensorFlow 1.x and 2.x

3. Regression

4. Convolutional Neural Networks

5. Advanced Convolutional Neural Networks

6. Generative Adversarial Networks

7. Word Embeddings

8. Recurrent Neural Networks

9. Autoencoders

10. Unsupervised Learning

11. Reinforcement Learning

12. TensorFlow and Cloud

13. TensorFlow for Mobile and IoT and TensorFlow.js

14. An introduction to AutoML

15. The Math Behind Deep Learning

16. Tensor Processing Unit

17. Other Books You May Enjoy

18. Index

Virtual machines on cloud

As the name suggests, virtual machines (VMs) are not real systems. Instead, they are a computer file, called an image, which emulates the behavior of an actual computer. Thus, we can create a virtual computer within a computer. It runs on your existing OS, almost like any other program, providing you the same experience as you would have on a physical system with the same configuration (albeit with some latency).

Each virtual machine has its own virtual hardware, including CPUs, GPUs, memory, hard drives, network interfaces, and other devices. The cloud service providers allow you to create a virtual machine on their physical hardware using VM services. This section will cover how to create a virtual machine on the three cloud service providers, and features offered by them.

EC2 on Amazon

To create a virtual machine on Amazon EC2 you will need to launch an Amazon EC2 instance by clicking on the Launch Instance button available in the EC2 dashboard...

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Authors (3)

Antonio Gulli

Antonio Gulli has a passion for establishing and managing global technological talent for innovation and execution. His core expertise is in cloud computing, deep learning, and search engines. Currently, Antonio works for Google in the Cloud Office of the CTO in Zurich, working on Search, Cloud Infra, Sovereignty, and Conversational AI.

See other products by Antonio Gulli

Amita Kapoor

Amita Kapoor is an accomplished AI consultant and educator, with over 25 years of experience. She has received international recognition for her work, including the DAAD fellowship and the Intel Developer Mesh AI Innovator Award. She is a highly respected scholar in her field, with over 100 research papers and several best-selling books on deep learning and AI. After teaching for 25 years at the University of Delhi, Amita took early retirement and turned her focus to democratizing AI education. She currently serves as a member of the Board of Directors for the non-profit Neuromatch Academy, fostering greater accessibility to knowledge and resources in the field. Following her retirement, Amita also founded NePeur, a company that provides data analytics and AI consultancy services. In addition, she shares her expertise with a global audience by teaching online classes on data science and AI at the University of Oxford.

Read more

See other products by Amita Kapoor

Sujit Pal

Sujit Pal is a Technology Research Director at Elsevier Labs, an advanced technology group within the Reed-Elsevier Group of companies. His interests include semantic search, natural language processing, machine learning, and deep learning. At Elsevier, he has worked on several initiatives involving search quality measurement and improvement, image classification and duplicate detection, and annotation and ontology development for medical and scientific corpora.

See other products by Sujit Pal

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