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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

References

  1. Quantization-aware training https://github.com/tensorflow/tensorflow/tree/r1.13/tensorflow/contrib/quantize
  2. Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference, Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew Howard, Hartwig Adam, Dmitry Kalenichenko (Submitted on 15 Dec 2017); https://arxiv.org/abs/1712.05877
  3. MobileNetV2: Inverted Residuals and Linear Bottlenecks, Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen (Submitted on 13 Jan 2018 (v1), last revised 21 Mar 2019 (v4)) https://arxiv.org/abs/1806.08342
  4. MnasNet: Platform-Aware Neural Architecture Search for Mobile, Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, Quoc V. Le https://arxiv.org/abs/1807.11626
  5. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs, Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos...
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83
Tech Concepts
36
Programming languages
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Deep Learning with TensorFlow 2 and Keras
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