Angular and Machine Learning Pocket Primer

By: Oswald Campesato

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Paperback | 11 April 2020

At a Glance

Paperback
280 Pages

Dimensions(cm)
22.86 x 15.24 x 1.91

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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.

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