Angular and Machine Learning Pocket Primer

by Oswald Campesato

Overview

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

Product Details

ISBN-13:	9781683924692
Publisher:	Mercury Learning & Information
Publication date:	03/27/2020
Series:	Pocket Primer
Sold by:	Barnes & Noble
Format:	eBook
Pages:	262
File size:	2 MB

About the Author

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

Table of Contents

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.