Angular and Deep Learning Pocket Primer - by Oswald Campesato (Paperback)

About the Book

As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to basic deep learning concepts and incorporate that knowledge into Angular 10 applications. It is intended to be a fast-paced introduction to some basic features of deep learning and an overview of several popular deep learning classifiers. The book inc

Book Synopsis

No detailed description available for "Angular and Deep Learning Pocket Primer".

Review Quotes

Bookwatch:

"Adding to the Pocket Primer series is a fine introduction to basic deep learning approaches to Angular 10 applications, offering computer users a fast way to applying knowledge to real-world activities. Computer users should expect discussions of basic deep learning concepts, accompanied by algorithms and code files that demonstrate how these concepts work in the Angular 10 environment. Chapters cover TensorFlow 2 and Keras as they examine subjects such as pipes and UI controls, data binding models, architectures for deep learning, and creating histograms, heat maps, and more. Those seeking a quick learning approach to Angular and the deep learning environment will find this pocket primer's examples and references lend nicely to refresher courses and new introductions alike."

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).