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Synthetic Data for Deep Learning - Generate Synthetic Data for Decision Making and Applications with Python and R (Paperback, 1st ed.)
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Synthetic Data for Deep Learning - Generate Synthetic Data for Decision Making and Applications with Python and R (Paperback, 1st ed.)
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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. What You Will Learn
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 Who This Book Is For Those 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.
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