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Hands-On Deep Learning for IoT - Train neural network models to develop intelligent IoT applications (Paperback)
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Hands-On Deep Learning for IoT - Train neural network models to develop intelligent IoT applications (Paperback)
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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 DescriptionArtificial 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. What you will learn Get acquainted with different
neural network architectures and their suitability in IoT
Understand how deep learning can improve the predictive power in
your IoT solutions Capture and process streaming data for
predictive maintenance Select optimal frameworks for image
recognition and indoor localization Analyze voice data for speech
recognition in IoT applications Develop deep learning-based IoT
solutions for healthcare Enhance security in your IoT solutions
Visualize analyzed data to uncover insights and perform accurate
predictions Who this book is forIf you're an IoT developer, data
scientist, or deep learning enthusiast who wants to apply deep
learning techniques to build smart IoT applications, this book is
for you. Familiarity with machine learning, a basic understanding
of the IoT concepts, and some experience in Python programming will
help you get the most out of this book.
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