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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

TPUs are very special ASIC chips developed at Google for executing neural network mathematical operations in an ultra-fast manner. The core of the computation is a systolic multiplier that computes multiple dot products (row * column) in parallel, thus accelerating the computation of basic deep learning operations. Think of a TPU as a special-purpose coprocessor for deep learning, which is focused on matrix or tensor operations. Google has announced three generations of TPUs so far, plus an additional Edge TPU for IoT. Cloud TPU v1 is a PCI-based specialized co-processor, with 92 TeraFLOPS and inference only. Cloud TPU v2 achieves 180 TeraFLOPS and it supports training and inference. Cloud TPU v2 pods released in alpha in 2018 can achieve 11.5 PetaFLOPS. Cloud TPU v3 achieves 420 TeraFLOPS with both training and inference support. Cloud TPU v3 pods can deliver more than 100 PetaFLOPS of computing power. That's a world-class supercomputer for tensor operations!

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83
Tech Concepts
36
Programming languages
73
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Deep Learning with TensorFlow 2 and Keras
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