TensorFlow Pocket Primer

by Oswald Campesato

Overview

No detailed description available for "TensorFlow Pocket Primer".

Product Details

ISBN-13:	9781683923640
Publisher:	Mercury Learning and Information
Publication date:	06/03/2019
Series:	Pocket Primer
Pages:	152
Product dimensions:	6.00(w) x 9.00(h) x (d)

About the Author

Campesato Oswald :

Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, TensorFlow, and NLP. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the NLP Using R Pocket Primer (all Mercury Learning and Information).

Table of Contents

1: Introduction to TensorFlow

2: Useful TensorFlow APIs

3: TensorFlow Datasets

4: Linear Regression

5: Logistic Regression

On The Companion Files!

(available from the publisher for downloading by writing to [e-mail])

• Source code samples
• Figures

Editorial Reviews

"TensorFlow Pocket Primer introduces readers to TensorFlow 1x basics for machine learning algorithms, and is designed to be an introduction used either to supplement a course or for self-learning. It uses Python to cover code examples, assumes limited experience and background in the subject, and comes with supporting reference files containing all source code examples as a download from the publisher. From Cloud-based platforms to useful components of TensorFlow and their real-world applications, this primer will get anyone up and running in the shortest amount of time possible."

From the Publisher

"TensorFlow Pocket Primer introduces readers to TensorFlow 1x basics for machine learning algorithms, and is designed to be an introduction used either to supplement a course or for self-learning. It uses Python to cover code examples, assumes limited experience and background in the subject, and comes with supporting reference files containing all source code examples as a download from the publisher. From Cloud-based platforms to useful components of TensorFlow and their real-world applications, this primer will get anyone up and running in the shortest amount of time possible."

Midwest Book Review