Pocket Primer Series Read Description

Angular and Machine Learning Pocket Primer

Mixed media product
April 2020
9781683924708
More details
  • Publisher
    Mercury Learning & Information
  • Published
    11th April
  • ISBN 9781683924708
  • Language English
  • Pages 262 pp.
  • Size 6" x 9"
$39.95
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March 2020
9781683924685
More details
  • Publisher
    Mercury Learning & Information
  • Published
    27th March
  • ISBN 9781683924685
  • Language English
  • Pages 262 pp.
  • Size 6" x 9"
$179.95
E-Book (ePub)
March 2020
9781683924692
More details
  • Publisher
    Mercury Learning & Information
  • Published
    27th March
  • 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 (Also available from the publisher for downloading by writing to info@merclearning.com)

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) specializes in Deep Learning, Data Cleaning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow Pocket Primer; Artificial Intelligence, Machine Learning, and Deep LearningAndroid Pocket Primer, Angular4 Pocket Primer, and the Python Pocket Primer (Mercury Learning).