Synthetic Data for Deep Learning (Paperback)
Language: English
Published by APress, Berkley, 2023
- First Edition
- Softcover
- New
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
AbeBooks seller since October 12, 2005
Condition: New
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Add to basketItem description from seller
Paperback. Data is the indispensable fuel that drives the decision making of everything from governments, to major corporations, to sports teams. Its value is almost beyond measure. But what if that data is either unavailable or problematic to access? Thats where synthetic data comes in. This book will show you how to generate synthetic data and use it to maximum effect.Synthetic Data for Deep Learning begins by tracing the need for and development of synthetic data before delving into the role it plays in machine learning and computer vision. Youll gain insight into how synthetic data can be used to study the benefits of autonomous driving systems and to make accurate predictions about real-world data. Youll work through practical examples of synthetic data generation using Python and R, placing its purpose and methods in a real-world context. Generative Adversarial Networks (GANs) are also covered in detail, explaining how they work and their potential applications.After completing this book, youll have the knowledge necessary to generate and use synthetic data to enhance your corporate, scientific, or governmental decision making.What You Will LearnCreate synthetic tabular data with R and PythonUnderstand how synthetic data is important for artificial neural networksMaster the benefits and challenges of synthetic dataUnderstand concepts such as domain randomization and domain adaptation related to synthetic data generationWho This Book Is ForThose who want to learn about synthetic data and its applications, especially professionals working in the field of machine learning and computer vision. This book will also be useful for graduate and doctoral students interested in this subject. Beginning-Intermediate user level Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…
Seller Inventory # 9781484285862
- Title
- Synthetic Data for Deep Learning (Paperback)
- Author
- Necmi Guersakal
- Publisher
- APress, Berkley
- Publication year
- 2023
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1484285867
- ISBN 13
- 9781484285862
- Edition
- 1st Edition
Data is the indispensable fuel that drives the decision making of everything from governments, to major corporations, to sports teams. Its value is almost beyond measure. But what if that data is either unavailable or problematic to access? That’s where synthetic data comes in. This book will show you how to generate synthetic data and use it to maximum effect.
Synthetic Data for Deep Learning begins by tracing the need for and development of synthetic data before delving into the role it plays in machine learning and computer vision. You’ll gain insight into how synthetic data can be used to study the benefits of autonomous driving systems and to make accurate predictions about real-world data. You’ll work through practical examples of synthetic data generation using Python and R, placing its purpose and methods in a real-world context. Generative Adversarial Networks (GANs) are also covered in detail, explaining how they work and their potential applications.
After completing this book, you’ll have the knowledge necessary to generate and use synthetic data to enhance your corporate, scientific, or governmental decision making.- Create synthetic tabular data with R and Python
- Understand how synthetic data is important for artificial neural networks
- Master the benefits and challenges of synthetic data
- Understand concepts such as domain randomization and domain adaptation related to synthetic data generation
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
Grand Eagle Retail
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AbeBooks seller since October 12, 2005
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