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Advanced Deep Learning with TensorFlow 2 and Keras - Second Edition

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

Product type Book
Published in Feb 2020
Publisher Packt
ISBN-13 9781838821654
Pages 512 pages
Edition 2nd Edition
Languages
Author (1):
Rowel Atienza Rowel Atienza
Profile icon Rowel Atienza

Table of Contents (16) Chapters

Preface 1. Introducing Advanced Deep Learning with Keras 2. Deep Neural Networks 3. Autoencoders 4. Generative Adversarial Networks (GANs) 5. Improved GANs 6. Disentangled Representation GANs 7. Cross-Domain GANs 8. Variational Autoencoders (VAEs) 9. Deep Reinforcement Learning 10. Policy Gradient Methods 11. Object Detection 12. Semantic Segmentation 13. Unsupervised Learning Using Mutual Information 14. Other Books You May Enjoy
15. Index

5. Conclusion

In this chapter, we've presented the Functional API as an advanced method for building complex deep neural network models using tf.keras. We also demonstrated how the Functional API could be used to build the multi-input-single-output Y-Network. This network, when compared to a single branch CNN network, achieves better accuracy. For the rest of the book, we'll find the Functional API indispensable in building more complex and advanced models. For example, in the next chapter, the Functional API will enable us to build a modular encoder, decoder, and autoencoder.

We also spent a significant amount of time exploring two important deep networks, ResNet and DenseNet. Both of these networks have been used not only in classification but also in other areas, such as segmentation, detection, tracking, generation, and visual semantic understanding. In Chapter 11, Object Detection, and Chapter 12, Semantic Segmentation, we will use ResNet for object detection and...

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Advanced Deep Learning with TensorFlow 2 and Keras - Second Edition
Published in: Feb 2020 Publisher: Packt ISBN-13: 9781838821654
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