| 书目名称 | Synthetic Data for Deep Learning | | 副标题 | Generate Synthetic D | | 编辑 | Necmi Gürsakal,Sadullah Çelik,Esma Birişçi | | 视频video | | | 概述 | Explains how to debug and optimize advanced neural network architectures such as CNN and RNN.Covers how synthetic data can be used to benefit autonomous driving systems.Includes various types of GANs, | | 图书封面 |  | | 描述 | .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 | | 出版日期 | Book 2022 | | 关键词 | Deep Learning; Artificial Intelligence; Python; R; Synthetic Data; Neural Networks; Generative Adversarial | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4842-8587-9 | | isbn_softcover | 978-1-4842-8586-2 | | isbn_ebook | 978-1-4842-8587-9 | | copyright | Necmi G�rsakal, Sadullah �elik, and Esma Biri?�i 2022 |
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发表于 2025-3-21 17:55:41
