Deep Learning and Practice with MindSpore
This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore AI computing framework. Divided into 14 chapters, the book covers deep learning, deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neur...
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| Format: | eBook |
| Language: | English |
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Singapore
Springer Nature Singapore
2021, 2021
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| Edition: | 1st ed. 2021 |
| Series: | Cognitive Intelligence and Robotics
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
| Summary: | This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore AI computing framework. Divided into 14 chapters, the book covers deep learning, deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), unsupervised learning, deep reinforcement learning, automated machine learning, device-cloud collaboration, deep learning visualization, and data preparation for deep learning. To help clarify the complex topics discussed, this book includes numerous examples and links to online resources |
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| Physical Description: | XVIII, 394 p. 357 illus., 13 illus. in color online resource |
| ISBN: | 9789811622335 |