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Learn TensorFlow 2.0 : Implement Machine Learning and Deep Learning Models with Python

By: (Author) Avinash Manure , (Author) Pramod Singh

Extended Catalogue

Ksh 7,200.00

Format: Paperback or Softback

ISBN-10: 1484255607

ISBN-13: 9781484255605

Publisher: APress

Imprint: APress

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Jan 5th, 2020

Print length: 164 Pages

Weight: 298 grams

Dimensions (height x width x thickness): 15.50 x 23.30 x 1.70 cms

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  • Description

  • Reviews

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 LearnReview the new features of TensorFlow 2.0Use TensorFlow 2.0 to build machine learning and deep learning models Perform sequence predictions using TensorFlow 2.0Deploy TensorFlow 2.0 models with practical examplesWho This Book Is ForData scientists, machine and deep learning engineers.
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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