Pocket Primer Series Read Description

Angular and Deep Learning Pocket Primer

Paperback
November 2020
9781683924739
More details
  • Publisher
    Mercury Learning and Information
  • Published
    16th November 2020
  • ISBN 9781683924739
  • Language English
  • Pages 342 pp.
  • Size 6" x 9"
$39.95
Lib E-Book

Library E-Books

We are signed up with aggregators who resell networkable e-book editions of our titles to academic libraries. These editions, priced at par with simultaneous hardcover editions of our titles, are not available direct from Stylus.

These aggregators offer a variety of plans to libraries, such as simultaneous access by multiple library patrons, and access to portions of titles at a fraction of list price under what is commonly referred to as a "patron-driven demand" model.

October 2020
9781683924715
More details
  • Publisher
    Mercury Learning and Information
  • Published
    13th October 2020
  • ISBN 9781683924715
  • Language English
  • Pages 342 pp.
  • Size 6" x 9"
$179.95
E-Book

E-books are now distributed via RedShelf or VitalSource

You will choose the vendor in the cart as part of the check out process. These vendors offer a more seamless way to access the ebook, and add some great new features including text-to-voice. You own your ebook for life, it is simply hosted on the vendors website, working much like Kindle and Nook. Click here to see more detailed information on this process.

October 2020
9781683924722
More details
  • Publisher
    Mercury Learning and Information
  • Published
    13th October 2020
  • ISBN 9781683924722
  • Language English
  • Pages 342 pp.
  • Size 6" x 9"
$39.95

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.
The companion files are also available online by emailing the publisher with proof of purchase at info@merclearning.com.

"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."

Bookwatch

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

Oswald Campesato

Oswald Campesato specializes in Deep Learning, Python, and GPT-4. He is the author/co-author of over forty books including Python 3 Data Visualization Using ChatGPT / GPT-4, NLP for Developers, and Artificial Intelligence, Machine Learning and Deep Learning (all Mercury Learning).