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Angular and Machine Learning

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Angular and Machine Learning Synopsis

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, Naïve 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 This Edition

ISBN: 9781683924708
Publication date:
Author: Oswald Campesato
Publisher: Mercury Learning & Information an imprint of Mercury Learning and Information
Format: Paperback
Pagination: 200 pages
Series: Pocket Primer
Genres: Neural networks and fuzzy systems
Human–computer interaction
Artificial intelligence

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