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Deep Learning with TensorFlow 2 and Keras

Deep Learning with TensorFlow 2 and Keras - Second Edition

By : Antonio Gulli, Dr. Amita Kapoor, Sujit Pal
4.3 (26)
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Deep Learning with TensorFlow 2 and Keras

Deep Learning with TensorFlow 2 and Keras

4.3 (26)
By: Antonio Gulli, Dr. 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)
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17
Other Books You May Enjoy
18
Index

Summary

In this chapter we have seen many applications of CNNs across very different domains, from traditional image processing and computer vision, to close-enough video processing, to not-so-close audio processing and text processing. In a relatively few number of years, CNNs took machine learning by storm.

Nowadays it is not uncommon to see multimodal processing, where text, images, audio, and videos are considered together to achieve better performance, frequently by means of CNNs together with a bunch of other techniques such as RNNs and reinforcement learning. Of course, there is much more to consider, and CNNs have recently been applied to many other domains such as Genetic inference [13], which are, at least at first glance, far away from the original scope of their design.

In this chapter, we have discussed all the major variants of ConvNets. In the next chapter, we will introduce Generative Nets: one of the most innovative deep learning architectures yet.

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Tech Concepts
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Deep Learning with TensorFlow 2 and Keras
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