Angular and Deep Learning Pocket Primer: Pocket Primer
Autor Oswald Campesatoen Limba Engleză Paperback – 15 noi 2020
- 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.
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Specificații
ISBN-13: 9781683924739
ISBN-10: 1683924738
Pagini: 342
Dimensiuni: 152 x 229 x 20 mm
Greutate: 0.52 kg
Editura: Mercury Learning & Information
Colecția Pocket Primer
Seria Pocket Primer
ISBN-10: 1683924738
Pagini: 342
Dimensiuni: 152 x 229 x 20 mm
Greutate: 0.52 kg
Editura: Mercury Learning & Information
Colecția Pocket Primer
Seria Pocket Primer
Notă biografică
Campesato Oswald : Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, TensorFlow, and NLP. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the NLP Using R Pocket Primer (all Mercury Learning and Information).
Cuprins
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
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