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Learn TensorFlow 2.0 - Implement Machine Learning and Deep Learning Models with Python (Paperback, 1st ed.)
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Learn TensorFlow 2.0 - Implement Machine Learning and Deep Learning Models with Python (Paperback, 1st ed.)
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Learn how to use TensorFlow 2.0 to build machine learning and deep
learning models with complete examples. The book begins with
introducing TensorFlow 2.0 framework and the major changes from its
last release. Next, it focuses on building Supervised Machine
Learning models using TensorFlow 2.0. It also demonstrates how to
build models using customer estimators. Further, it explains how to
use TensorFlow 2.0 API to build machine learning and deep learning
models for image classification using the standard as well as
custom parameters. You'll review sequence predictions, saving,
serving, deploying, and standardized datasets, and then deploy
these models to production. All the code presented in the book will
be available in the form of executable scripts at Github which
allows you to try out the examples and extend them in interesting
ways. What You'll Learn Review the new features of TensorFlow 2.0
Use TensorFlow 2.0 to build machine learning and deep learning
models Perform sequence predictions using TensorFlow 2.0 Deploy
TensorFlow 2.0 models with practical examples Who This Book Is For
Data scientists, machine and deep learning engineers.
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