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Deep learning and practice with Mind...
~
Chen, Lei.
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Deep learning and practice with MindSpore
Record Type:
Electronic resources : Monograph/item
Title/Author:
Deep learning and practice with MindSpore/ by Lei Chen.
Author:
Chen, Lei.
Published:
Singapore :Springer Singapore : : 2021.,
Description:
xviii, 394 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:
Chapter 1. Introduction -- Chapter 2. Deep Learning Basics -- Chapter 3. DNN -- Chapter 4. Training of DNNs -- Chapter 5. Convolutional Neural Network -- Chapter 6. RNN -- Chapter 7. Unsupervised Learning: Word Vector -- Chapter 8. Unsupervised Learning: Graph Vector -- Chapter 9. Unsupervised Learning: Deep Generative Model -- Chapter 10. Deep Reinforcement Learning -- Chapter 11. Automated Machine Learning -- Chapter 12. Device-Cloud Collaboration -- Chapter 13. Deep Learning Visualization -- Chapter 14. Data Preparation for Deep Learning.
Contained By:
Springer Nature eBook
Subject:
Machine learning. -
Online resource:
https://doi.org/10.1007/978-981-16-2233-5
ISBN:
9789811622335
Deep learning and practice with MindSpore
Chen, Lei.
Deep learning and practice with MindSpore
[electronic resource] /by Lei Chen. - Singapore :Springer Singapore :2021. - xviii, 394 p. :ill. (some col.), digital ;24 cm. - Cognitive intelligence and robotics,2520-1964. - Cognitive intelligence and robotics..
Chapter 1. Introduction -- Chapter 2. Deep Learning Basics -- Chapter 3. DNN -- Chapter 4. Training of DNNs -- Chapter 5. Convolutional Neural Network -- Chapter 6. RNN -- Chapter 7. Unsupervised Learning: Word Vector -- Chapter 8. Unsupervised Learning: Graph Vector -- Chapter 9. Unsupervised Learning: Deep Generative Model -- Chapter 10. Deep Reinforcement Learning -- Chapter 11. Automated Machine Learning -- Chapter 12. Device-Cloud Collaboration -- Chapter 13. Deep Learning Visualization -- Chapter 14. Data Preparation for Deep Learning.
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.
ISBN: 9789811622335
Standard No.: 10.1007/978-981-16-2233-5doiSubjects--Topical Terms:
533906
Machine learning.
LC Class. No.: Q325.5 / .C54 2021
Dewey Class. No.: 006.31
Deep learning and practice with MindSpore
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Chapter 1. Introduction -- Chapter 2. Deep Learning Basics -- Chapter 3. DNN -- Chapter 4. Training of DNNs -- Chapter 5. Convolutional Neural Network -- Chapter 6. RNN -- Chapter 7. Unsupervised Learning: Word Vector -- Chapter 8. Unsupervised Learning: Graph Vector -- Chapter 9. Unsupervised Learning: Deep Generative Model -- Chapter 10. Deep Reinforcement Learning -- Chapter 11. Automated Machine Learning -- Chapter 12. Device-Cloud Collaboration -- Chapter 13. Deep Learning Visualization -- Chapter 14. Data Preparation for Deep Learning.
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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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