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Artificial Neural Networks with TensorFlow 2

ANN Architecture Machine Learning Projects
BuchKartoniert, Paperback
726 Seiten
Englisch
Springererschienen am21.11.20201st ed.
This book offers a single source that provides comprehensive coverage of the capabilities of TensorFlow 2 through the use of realistic, scenario-based projects.After learning what's new in TensorFlow 2, you'll dive right into developing machine learning models through applicable projects.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR70,00
E-BookPDF1 - PDF WatermarkE-Book
EUR66,99

Produkt

KlappentextThis book offers a single source that provides comprehensive coverage of the capabilities of TensorFlow 2 through the use of realistic, scenario-based projects.After learning what's new in TensorFlow 2, you'll dive right into developing machine learning models through applicable projects.
Zusammenfassung
Tackle advanced neural network projects with TensorFlow

Hone a working knowledge of ANN architectures

Progress from deep learning beginner to experienced DL developer
Details
ISBN/GTIN978-1-4842-6149-1
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2020
Erscheinungsdatum21.11.2020
Auflage1st ed.
Seiten726 Seiten
SpracheEnglisch
Gewicht1124 g
IllustrationenXXIX, 726 p. 237 illus.
Artikel-Nr.48674319

Inhalt/Kritik

Inhaltsverzeichnis
Chapter 1: TensorFlow Jump Start.- Chapter 2: A Closer Look at TensorFlow.- Chapter 3: Deep Dive in tf.keras.- Chapter 4: Transfer Learning.- Chapter 5: Neutral Networks for Regression.- Chapter 6: Estimators.- Chapter 7: Text Generation.- Chapter 8: Language Translation.- Chapter 9: Natural Langauge.- Chapter 10: Image Captioning.- Chapter 11: Time Series.- Chapter 12: Style Transfer.- Chapter 13: Image Generation- Chapter 14: Image Translation.mehr

Autor

Poornachandra Sarang has 30+ years of IT experience and is an experienced author. His work has always focused on state-of-the-art and emerging technologies. He has provided consulting services to-Sun Microsystems, Microsoft, Oracle, and Hewlett-Packard. He has been a Ph.D. advisor for Computer Science and is currently on a Thesis Advisory Committee for students pursuing Ph.D. in Computer Engineering-setting the course curriculum for both under-graduate and post-graduate courses in Computer Science/Engineering. He has delivered seminars, written articles, and provided consulting recently on Machine Learning and Deep Learning. He maintains a machine learning blog at education.abcom.com.