Angular and Deep Learning Pocket Primer
1st Edition
Published on 27. October 2020
342 pages
978-1-68392-471-5 (ISBN)
Description
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 applications
- Covers 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 Keras
- Includes companion files with source code and 4-color figures.
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More details
Series
Language
English
Place of publication
Herndon, VA
United States
Target group
Professional and scholarly
US School Grade: College Graduate Student
File size
4,03 MB
ISBN-13
978-1-68392-471-5 (9781683924715)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Oswald Campesato
Angular and Deep Learning Pocket Primer
Book
11/2020
1st Edition
Mercury Learning & Information
€44.95
Article not available at the moment
Oswald Campesato
Angular and Deep Learning Pocket Primer
E-Book
10/2020
1st Edition
Mercury Learning and Information
€42.99
Available for download
Person
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).
Content
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
Appendices:
A. Introduction to Keras
B. Introduction to TensorFlow 2
C. TensorFlow 2 Datasets
Index
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
Appendices:
A. Introduction to Keras
B. Introduction to TensorFlow 2
C. TensorFlow 2 Datasets
Index
