Hands-On Deep Learning for IoT
Karim, MD Rezaul, Razzaque, Mohammad Abdur
- 出版商: Packt Publishing
- 出版日期: 2019-06-11
- 售價: $1,600
- 貴賓價: 9.5 折 $1,520
- 語言: 英文
- 頁數: 308
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1789616131
- ISBN-13: 9781789616132
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相關分類:
DeepLearning、物聯網 IoT
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相關翻譯:
物聯網深度學習 (簡中版)
商品描述
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About |
Artificial Intelligence is growing quickly, which is driven by advancements in neural networks(NN) and deep learning (DL). With an increase in investments in smart cities, smart healthcare, and industrial Internet of Things (IoT), commercialization of IoT will soon be at peak in which massive amounts of data generated by IoT devices need to be processed at scale. Hands-On Deep Learning for IoT will provide deeper insights into IoT data, which will start by introducing how DL fits into the context of making IoT applications smarter. It then covers how to build deep architectures using TensorFlow, Keras, and Chainer for IoT. You’ll learn how to train convolutional neural networks(CNN) to develop applications for image-based road faults detection and smart garbage separation, followed by implementing voice-initiated smart light control and home access mechanisms powered by recurrent neural networks(RNN). You’ll master IoT applications for indoor localization, predictive maintenance, and locating equipment in a large hospital using autoencoders, DeepFi, and LSTM networks. Furthermore, you’ll learn IoT application development for healthcare with IoT security enhanced. By the end of this book, you will have sufficient knowledge need to use deep learning efficiently to power your IoT-based applications for smarter decision making. |
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