Angular and Deep Learning Pocket Primer / / Oswald Campesato.

• VerfasserIn: Campesato, Oswald,
• Place / Publishing House: Dulles, VA : : Mercury Learning and Information, , [2020]; ©2020
• Year of Publication: 2020
• Language: English
• Series: Pocket Primer
• Physical Description: 1 online resource (342 p.)
• Other title: Frontmatter --; Contents --; Preface --; 1. Quick Introduction to Angular --; 2. UI Controls, User Input, and Pipes --; 3. Forms and Services --; 4. Deep Learning Introduction --; 5. Deep Learning: RNNs and LSTMs --; 6. Angular and Tensorflow.JS --; Appendix A. Introduction to KERAS --; Appendix B. Introduction to TF 2 --; Appendix C. TF 2 Datasets --; Index
• Format: Mode of access: Internet via World Wide Web.
• ISBN: 9781683924715
• Access: restricted access
• Hierarchical level: Monograph
• Statement of Responsibility: Oswald Campesato.

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 includes code samples and numerous figures and covers topics such as Angular 10 functionality, basic deep learning concepts, classification algorithms, TensorFlow, and Keras. Companion files with code and color figures are included. FEATURES:Introduces basic deep learning concepts and Angular 10 applicationsCovers MLPs (MultiLayer Perceptrons) and CNNs (Convolutional Neural Networks), RNNs (Recurrent Neural Networks), LSTMs (Long Short-Term Memory), GRUs (Gated Recurrent Units), autoencoders, and GANs (Generative Adversarial Networks)Introduces TensorFlow 2 and KerasIncludes companion files with source code and 4-color figures.The companion files are also available online by emailing the publisher with proof of purchase at [e-mail].