Angular and Deep Learning Pocket Primer
(Sprache: Englisch)
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Produktinformationen zu „Angular and Deep Learning Pocket Primer “
No detailed description available for "Angular and Deep Learning Pocket Primer".
Inhaltsverzeichnis zu „Angular and Deep Learning Pocket Primer “
1: Quick Introduction to Angular2: 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
Autoren-Porträt von Oswald Campesato
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).
Bibliographische Angaben
- Autor: Oswald Campesato
- 2020, 342 Seiten, Maße: 15,2 x 22,9 cm, Kartoniert (TB), Englisch
- Verlag: De Gruyter
- ISBN-10: 1683924738
- ISBN-13: 9781683924739
Sprache:
Englisch
Pressezitat
Bookwatch:"Adding to the Pocket Primer series is a fine introduction to basic deep learning approaches to Angular 10 applications, offering computer users a fast way to applying knowledge to real-world activities. Computer users should expect discussions of basic deep learning concepts, accompanied by algorithms and code files that demonstrate how these concepts work in the Angular 10 environment. Chapters cover TensorFlow 2 and Keras as they examine subjects such as pipes and UI controls, data binding models, architectures for deep learning, and creating histograms, heat maps, and more. Those seeking a quick learning approach to Angular and the deep learning environment will find this pocket primer's examples and references lend nicely to refresher courses and new introductions alike."
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