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Paperback
May 2020
9781683924739
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- Publisher
Mercury Learning & Information - ISBN 9781683924739
- Language English
- Pages 200 pp.
- Size 6" x 9"
$39.95
E-Book
May 2020
9781683924722
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- Publisher
Mercury Learning & Information - ISBN 9781683924722
- Language English
- Pages 200 pp.
- Size 6" x 9"
$34.95
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May 2020
9781683924715
More details
- Publisher
Mercury Learning & Information - ISBN 9781683924715
- Language English
- Pages 200 pp.
- Size 6" x 9"
$179.95
This book provides readers with enough information for them to develop more sophisticated Angular applications that incorporate deep learning. The first three chapters of this book contain a short tour of basic Angular functionality, such as UI components and forms in Angular applications. The fourth chapter introduces you to deep learning, the problems it can solve, and some challenges for the future. You will also learn about MLPs (MultiLayer Perceptrons), CNNs (Convolutional Neural Networks), and a Keras-based code sample of a CNN with the MNIST dataset. The fifth chapter discusses RNNs (Recurrent Neural Networks), BPTT (Back Propagation Through Time), as well as LSTMs (Long Short Term Memory) and AEs (Auto Encoders). The sixth chapter introduces basic TensorFlow concepts, followed by tensorflowjs (i.e., TensorFlow in modern browsers), and some examples of Angular applications combined with deep learning.
Oswald Campesato
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).