Angular 6 7 Pocket Primer


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Angular and Deep Learning Pocket Primer


Angular and Deep Learning Pocket Primer

Author: Oswald Campesato

language: en

Publisher: Mercury Learning and Information

Release Date: 2020-10-13


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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 4 Pocket Primer


Angular 4 Pocket Primer

Author: Oswald Campesato

language: en

Publisher: Walter de Gruyter GmbH & Co KG

Release Date: 2017-07-26


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No detailed description available for "Angular 4 Pocket Primer".

Angular and Machine Learning Pocket Primer


Angular and Machine Learning Pocket Primer

Author: Oswald Campesato

language: en

Publisher: Mercury Learning and Information

Release Date: 2020-03-27


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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