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Hands-On Deep Learning for Images with TensorFlow - Build intelligent computer vision applications using TensorFlow and Keras (Paperback)
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Hands-On Deep Learning for Images with TensorFlow - Build intelligent computer vision applications using TensorFlow and Keras (Paperback)
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Explore TensorFlow's capabilities to perform efficient deep
learning on images Key Features Discover image processing for
machine vision Build an effective image classification system using
the power of CNNs Leverage TensorFlow's capabilities to perform
efficient deep learning Book DescriptionTensorFlow is Google's
popular offering for machine learning and deep learning, quickly
becoming a favorite tool for performing fast, efficient, and
accurate deep learning tasks. Hands-On Deep Learning for Images
with TensorFlow shows you the practical implementations of
real-world projects, teaching you how to leverage TensorFlow's
capabilities to perform efficient image processing using the power
of deep learning. With the help of this book, you will get to grips
with the different paradigms of performing deep learning such as
deep neural nets and convolutional neural networks, followed by
understanding how they can be implemented using TensorFlow. By the
end of this book, you will have mastered all the concepts of deep
learning and their implementation with TensorFlow and Keras. What
you will learn Build machine learning models particularly focused
on the MNIST digits Work with Docker and Keras to build an image
classifier Understand natural language models to process text and
images Prepare your dataset for machine learning Create classical,
convolutional, and deep neural networks Create a RESTful image
classification server Who this book is forHands-On Deep Learning
for Images with TensorFlow is for you if you are an application
developer, data scientist, or machine learning practitioner looking
to integrate machine learning into application software and master
deep learning by implementing practical projects in TensorFlow.
Knowledge of Python programming and basics of deep learning are
required to get the best out of this book.
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