Deep Learning and Practice with MindSpore
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Beschreibung
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.
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.
Introduces readers to deep learning models and algorithms in both theory and practice Explores how deep learning methods can be used in various applications and their performance in this regard Combines theory and practical applications to explain how to implement high-performance deep learning models and achieves effective learning with MindSpore, Huawei's self-developed deep learning computing framework
Autor*in
Lei Chen
Themen in »Deep Learning and Practice with MindSpore«
Deep Learning MindSpore 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 Data Preparation