Pocket Primer Series Read Description

Angular and Machine Learning Pocket Primer

Paperback
April 2020
9781683924708
More details
  • Publisher
    Mercury Learning and Information
  • Published
    11th April 2020
  • ISBN 9781683924708
  • Language English
  • Pages 262 pp.
  • Size 6" x 9"
$39.95
Lib E-Book

Library E-Books

We are signed up with aggregators who resell networkable e-book editions of our titles to academic libraries. These editions, priced at par with simultaneous hardcover editions of our titles, are not available direct from Stylus.

These aggregators offer a variety of plans to libraries, such as simultaneous access by multiple library patrons, and access to portions of titles at a fraction of list price under what is commonly referred to as a "patron-driven demand" model.

March 2020
9781683924685
More details
  • Publisher
    Mercury Learning and Information
  • Published
    27th March 2020
  • ISBN 9781683924685
  • Language English
  • Pages 262 pp.
  • Size 6" x 9"
$179.95
E-Book (ePub)
March 2020
9781683924692
More details
  • Publisher
    Mercury Learning and Information
  • Published
    27th March 2020
  • ISBN 9781683924692
  • Language English
  • Pages 262 pp.
  • Size 6" x 9"
$34.95

As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to basic machine learning concepts and incorporate that knowledge into Angular applications. The book is intended to be a fast-paced introduction to some basic features of machine learning and an overview of several popular machine learning classifiers. It includes code samples and numerous figures and covers topics such as Angular functionality, basic machine learning concepts, classification algorithms, TensorFlow and Keras. The files with code and color figures are on the companion disc with the book or available from the publisher.

Features:

  • Introduces the basic machine learning concepts and Angular applications
  • Includes source code and full color figures

1: Quick Introduction to Angular
2: UI Controls, User Input, and Pipe
3: Forms and Services
4: Introduction to Machine Learning
5: Working with Classifiers
6: Angular and TensorFlow .js
Appendix: Introduction to Keras.

Oswald Campesato

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