Deep Learning for Computer Vision with SAS : An Introduction
Language: English
Published by SAS Institute Jun 2020, 2020
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
US$ 42.09
Quantity: 2 available
Add to basketItem description from seller
Neuware - Discover deep learning and computer vision with SAS! Deep Learning for Computer Vision with SAS(R): An Introduction introduces the pivotal components of deep learning. Readers will gain an in-depth understanding of how to build deep feedforward and convolutional neural networks, as well as variants of denoising autoencoders. Transfer learning is covered to help readers learn about this emerging field. Containing a mix of theory and application, this book will also briefly cover methods for customizing deep learning models to solve novel business problems or answer research questions. SAS programs and data are included to reinforce key concepts and allow readers to follow along with included demonstrations. Readers will learn how to: - Define and understand deep learning - Build models using deep learning techniques and SAS Viya - Apply models to score (inference) new data - Modify data for better analysis results - Search the hyperparameter space of a deep learning model - Leverage transfer learning using supervised and unsupervised methods. …
Seller Inventory # 9781642959154
- Title
- Deep Learning for Computer Vision with SAS : An Introduction
- Author
- Robert Blanchard
- Publisher
- SAS Institute Jun 2020
- Publication year
- 2020
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1642959154
- ISBN 13
- 9781642959154
- Item weight
- 268 grams
- Dimensions
- 235x191x8 mm
Deep Learning for Computer Vision with SAS®: An Introduction introduces the pivotal components of deep learning. Readers will gain an in-depth understanding of how to build deep feedforward and convolutional neural networks, as well as variants of denoising autoencoders. Transfer learning is covered to help readers learn about this emerging field. Containing a mix of theory and application, this book will also briefly cover methods for customizing deep learning models to solve novel business problems or answer research questions. SAS programs and data are included to reinforce key concepts and allow readers to follow along with included demonstrations.
Readers will learn how to:
- Define and understand deep learning
- Build models using deep learning techniques and SAS Viya
- Apply models to score (inference) new data
- Modify data for better analysis results
- Search the hyperparameter space of a deep learning model
- Leverage transfer learning using supervised and unsupervised methods
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
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