Learn Tensorflow 2.0: Implement Machine Learning and Deep Learning Models with Python
| AUTHOR | Manure, Avinash; Singh, Pramod |
| PUBLISHER | Apress (01/05/2020) |
| PRODUCT TYPE | Paperback (Paperback) |
Description
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
Who This Book Is For
Data scientists, machine and deep learning engineers.
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.
Show More
Product Format
Product Details
ISBN-13:
9781484255605
ISBN-10:
1484255607
Binding:
Paperback or Softback (Trade Paperback (Us))
Content Language:
English
More Product Details
Page Count:
164
Carton Quantity:
42
Product Dimensions:
6.14 x 0.39 x 9.21 inches
Weight:
0.58 pound(s)
Feature Codes:
Illustrated
Country of Origin:
NL
Subject Information
BISAC Categories
Computers | Artificial Intelligence - General
Computers | Languages - Python
Computers | Programming - Open Source
Dewey Decimal:
005.133
Descriptions, Reviews, Etc.
jacket back
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.
You will:
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.
You will:
- 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
Show More
publisher marketing
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
Who This Book Is For
Data scientists, machine and deep learning engineers.
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.
Show More
List Price $44.99
Your Price
$32.39