Angular and Deep Learning Pocket Primer (Computing)

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.

Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Data Cleaning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow Pocket Primer; Artificial Intelligence, Machine Learning, and Deep Learning; Android Pocket Primer, Angular4 Pocket Primer, and the Python Pocket Primer (Mercury Learning).