512,27 €
569,19 €
-10% with code: EXTRA
Deep Learning and Practice with Mindspore
Deep Learning and Practice with Mindspore
512,27
569,19 €
  • We will send in 10–14 business days.
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…
  • Publisher:
  • ISBN-10: 9811622353
  • ISBN-13: 9789811622359
  • Format: 15.6 x 23.4 x 2.2 cm, softcover
  • Language: English
  • SAVE -10% with code: EXTRA

Deep Learning and Practice with Mindspore (e-book) (used book) | bookbook.eu

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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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  • Author: Lei Chen
  • Publisher:
  • ISBN-10: 9811622353
  • ISBN-13: 9789811622359
  • Format: 15.6 x 23.4 x 2.2 cm, softcover
  • Language: English English

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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