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lgli/深度学习应用手册.pdf
深度学习应用手册 🔍
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英语 [en] · 中文 [zh] · PDF · 12.4MB · 2019 · 📘 非小说类图书 · 🚀/lgli/lgrs · Save
描述
"This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain-computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars." -- prové de l'editor
备用文件名
lgrsnf/深度学习应用手册.pdf
备选标题
Handbook of Deep Learning Applications (Smart Innovation, Systems and Technologies (136))
备选作者
Valentina Emilia Balas; Sanjiban Sekhar Roy; Dharmendra Sharma; Pijush Samui; SpringerLink (Online service)
备选作者
Balas, Valentina Emilia; Roy, Sanjiban Sekhar; Sharma, Dharmendra; Samui, Pijush
备选作者
Dianjun Sun
备用出版商
Springer International Publishing : Imprint: Springer
备用出版商
Springer Nature Switzerland AG
备用版本
Smart innovation, systems, and technologies, volume 136, Cham, Switzerland, 2019
备用版本
Smart innovation, systems, and technologies, 136, 1st ed. 2019, Cham, 2019
备用版本
Smart innovation, systems and technologies, First edition, Cham, 2019
备用版本
Springer Nature, Cham, 2019
备用版本
1st ed. 2019, 2019-03-06
备用版本
Switzerland, Switzerland
备用版本
1st ed. 2019, PT, 2019
备用版本
Mar 06, 2019
备用版本
9, 20190225
元数据中的注释
Source title: Handbook of Deep Learning Applications (Smart Innovation, Systems and Technologies (136))
备用描述
This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain-computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph. D. scholars
备用描述
Smart Innovation, Systems and Technologies
Erscheinungsdatum: 06.03.2019
开源日期
2024-02-25
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