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.