The first three chapters of this book contain a short tour of basic Angular functionality, such as UI components and forms in Angular applications. The fourth chapter introduces you to machine learning concepts, such as supervised and unsupervised learning, followed by major types of machine learning algorithms (regression, classification, and clustering), along with a section regarding linear regression. The fifth chapter is devoted to classification algorithms, such as kNN, Naive Bayes, decision trees, random forests, and SVM (Support Vector Machines). The sixth chapter introduces basic TensorFlow concepts, followed by tensorflowjs (i.e., TensorFlow in modern browsers), and some examples of Angular applications combined with machine learning. In addition, this book contains an appendix for deep learning.

About the Author
Campesato Oswald :

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

Book Information
ISBN 9781683924708
Author Oswald Campesato
Format Paperback
Page Count 262
Imprint Mercury Learning & Information
Publisher Mercury Learning & Information
Weight(grams) 399g