- Publisher
Mercury Learning and Information - Published
11th April 2020 - ISBN 9781683924708
- Language English
- Pages 262 pp.
- Size 6" x 9"
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- Publisher
Mercury Learning and Information - Published
27th March 2020 - ISBN 9781683924685
- Language English
- Pages 262 pp.
- Size 6" x 9"
- Publisher
Mercury Learning and Information - Published
27th March 2020 - ISBN 9781683924692
- Language English
- Pages 262 pp.
- Size 6" x 9"
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) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, 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 Python Pocket Primer (Mercury Learning).