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Can I read Hands-On Deep Learning for IoT : Train Neural Network Models to Develop Intelligent IoT Applications on EtoBox?

Hands-On Deep Learning for IoT : Train Neural Network Models to Develop Intelligent IoT Applications by MD. Rezaul Karim, Mohammad Abdur Razzaque is a nonfiction available to read on EtoBox.

What is Hands-On Deep Learning for IoT : Train Neural Network Models to Develop Intelligent IoT Applications about?

Implement popular deep learning techniques to make your IoT applications smarter Key Features Understand how deep learning facilitates fast and accurate analytics in IoT Build intelligent voice and speech recognition apps in TensorFlow and Chainer Analyze IoT data for making automated decisions and efficient predictions Book Description 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 ligh

Who reads Hands-On Deep Learning for IoT : Train Neural Network Models to Develop Intelligent IoT Applications?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
MD. Rezaul Karim, Mohammad Abdur Razzaque
Publisher
Packt Publishing, Limited; Packt Publishing
Published
2019
Language
EN
ISBN
9781789616064
Category
nonfiction
Subjects
Computer Science, Science, Engineering

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