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Paperback
April 2020
9781683924708
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- Publisher
Mercury Learning & Information - ISBN 9781683924708
- Language English
- Pages 200 pp.
- Size 6" x 9"
$39.95
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April 2020
9781683924685
More details
- Publisher
Mercury Learning & Information - ISBN 9781683924685
- Language English
- Pages 200 pp.
- Size 6" x 9"
$179.95
E-Book
April 2020
9781683924692
More details
- Publisher
Mercury Learning & Information - ISBN 9781683924692
- Language English
- Pages 200 pp.
- Size 6" x 9"
$34.95
The first three chapters of the 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.
Oswald Campesato
Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Data Cleaning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow Pocket Primer; Artificial Intelligence, Machine Learning, and Deep Learning; Android Pocket Primer, Angular4 Pocket Primer, and the Python Pocket Primer (Mercury Learning).