- 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"
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- 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
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 specializes in Deep Learning, Python, Data Science, and generative AI. He is the author/co-author of over forty-five books including Google Gemini for Python, Large Language Models, and GPT-4 for Developers (all Mercury Learning).