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MERCURY LEARNING and INFORMATION provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets. We embrace both traditional and innovative publishing models designed to accommodate the needs of the intended audience by using the appropriate delivery methods.
Angular And Machine Learning Pocket Primer
ISBN: 9781683924708
Pub Date: April 2020
Specs: 7 x 9 Paperback
Pages: 300
Price: $39.95
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 a companion disc with source code and 4-color figures
BRIEF TOC
1: Quick Introduction to Angular. 2: UI Controls, User Input, and Pipes. 3: Forms and Services. 4: Introduction to Machine Learning. 5: Working with Classifiers. 6: Angular and TensorFlow.js. Appendix: Introduction to Keras.
ABOUT THE AUTHOR
Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the Python Pocket Primer (Mercury Learning).