Angular and Deep Learning Pocket Primer

Angular and Deep Learning Pocket Primer
Author: Oswald Campesato
Publsiher: Mercury Learning and Information
Total Pages: 360
Release: 2020-10-13
Genre: Computers
ISBN: 9781683924722

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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 [email protected].

Angular and Machine Learning Pocket Primer

Angular and Machine Learning Pocket Primer
Author: Oswald Campesato
Publsiher: Mercury Learning and Information
Total Pages: 261
Release: 2020-03-27
Genre: Computers
ISBN: 9781683924692

Download Angular and Machine Learning Pocket Primer Book in PDF, Epub and Kindle

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 source code and full color figures

Angular 4 Pocket Primer

Angular 4 Pocket Primer
Author: Oswald Campesato
Publsiher: Mercury Learning and Information
Total Pages: 352
Release: 2017-08-16
Genre: Computers
ISBN: 9781683920366

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As part of the best-selling Pocket Primer series, this book provides an overview of the major aspects and the source code to use the latest versions of Angular 4. It has coverage of the fundamental aspects of Angular that are illustrated via numerous code samples. This Pocket Primer is primarily for self-directed learners who want to learn Angular 4 programming, and it serves as a starting point for deeper exploration of its numerous applications. A companion disc (also available for downloading from the publisher) with source code and color images is included. FEATURES • Contains latest material on Angular 4, graphics/animation, mobile apps, • Includes companion files with all of the source code and images from the book • Provides coverage of the fundamental aspects of Angular4 that are illustrated via code samples BRIEF TABLE OF CONTENTS 1. A Quick Introduction to Angular. 2. UI Controls and User Input. 3. Graphics and Animation. 4. HTTP Requests and Routing. 5. Forms, Pipes, and Services. 6. Angular and Express. 7. Flux, Redux, GraphQL, Apollo, and Relay. 8. Angular and Mobile Apps. 9. Functional Reactive Programming. 10. Miscellaneous Topics. Index. ON THE COMPANION FILES! • Hundreds of source code samples • All images from the text (including 4-color) eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected].

Deep Learning Pocket Primer

Deep Learning Pocket Primer
Author: Oswald Campesato
Publsiher: Unknown
Total Pages: 135
Release: 2019-04-30
Genre: Electronic Book
ISBN: 1683923820

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R for Deep Learning Pocket Primer

R for Deep Learning Pocket Primer
Author: OSWALD. CAMPESATO
Publsiher: Unknown
Total Pages: 0
Release: 2023-12-14
Genre: Electronic Book
ISBN: 1683925521

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Angular 6 7 Pocket Primer

Angular 6 7 Pocket Primer
Author: Oswald Campesato
Publsiher: Unknown
Total Pages: 135
Release: 2019-10-31
Genre: Electronic Book
ISBN: 1683924185

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TensorFlow Pocket Primer

TensorFlow Pocket Primer
Author: Oswald Campesato
Publsiher: Mercury Learning and Information
Total Pages: 287
Release: 2019-05-09
Genre: Computers
ISBN: 9781683923657

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As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to TensorFlow 1.x fundamentals for basic machine learning algorithms in TensorFlow. It is intended to be a fast-paced introduction to various “core” features of TensorFlow, with code samples that cover deep learning and TensorFlow basics. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge. Companion files with all of the code samples are available for downloading from the publisher by writing to [email protected]. Features: Uses Python for code samples Covers TensorFlow APIs and Datasets Assumes the reader has very limited experience Companion files with all of the source code examples (download from the publisher)

TensorFlow 2 Pocket Primer

TensorFlow 2 Pocket Primer
Author: Oswald Campesato
Publsiher: Mercury Learning and Information
Total Pages: 229
Release: 2019-08-27
Genre: Computers
ISBN: 9781683924593

Download TensorFlow 2 Pocket Primer Book in PDF, Epub and Kindle

As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to basic machine learning algorithms using TensorFlow 2. It is intended to be a fast-paced introduction to various “core” features of TensorFlow, with code samples that cover machine learning and TensorFlow basics. A comprehensive appendix contains some Keras-based code samples and the underpinnings of MLPs, CNNs, RNNs, and LSTMs. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge. Companion files with all of the code samples are available for downloading from the publisher by emailing proof of purchase to [email protected]. Features: Uses Python for code samples Covers TensorFlow 2 APIs and Datasets Includes a comprehensive appendix that covers Keras and advanced topics such as NLPs, MLPs, RNNs, LSTMs Features the companion files with all of the source code examples and figures (download from the publisher)