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Deep Learning with TensorFlow 2 and Keras

You're reading from   Deep Learning with TensorFlow 2 and Keras Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API

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Product type Paperback
Published in Dec 2019
Publisher Packt
ISBN-13 9781838823412
Length 646 pages
Edition 2nd Edition
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Authors (3):
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Dr. Amita Kapoor Dr. Amita Kapoor
Author Profile Icon Dr. Amita Kapoor
Dr. Amita Kapoor
Sujit Pal Sujit Pal
Author Profile Icon Sujit Pal
Sujit Pal
Antonio Gulli Antonio Gulli
Author Profile Icon Antonio Gulli
Antonio Gulli
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Table of Contents (19) Chapters Close

Preface 1. Neural Network Foundations with TensorFlow 2.0 2. TensorFlow 1.x and 2.x FREE CHAPTER 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

TensorFlow Enterprise

TensorFlow Enterprise is the latest offering from Google that provides enterprise-grade support, cloud-scale performance, and managed services. TensorFlow Enterprise has been launched as a beta version. Its aim is to accelerate software development and ensure the reliability of launched AI applications. It is fully integrated with Google Cloud and its services, and introduces some improvements in the way TensorFlow Datasets reads data from Cloud Storage. TensorFlow Enterprise also introduces the BigQuery reader, which, as the name implies, allows the user to read data directly from BigQuery.

In ML tasks, speed is critical, and one of the major bottlenecks is the speed at which data is accessed for the training process. TensorFlow Enterprise provides optimized performance and easy access to data sources, making it extremely efficient on GCP.

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