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Introduces fundamental principles of deep learning with the explanation of basic elements required for understanding and applying deep learning models. Features coding structure using Python and PyTorch, presenting four typical deep learning case studies on image classification, object detection, semantic segmentation, and image captioning.

Introduces fundamental principles of deep learning with the explanation of basic elements required for understanding and applying deep learning models. Features coding structure using Python and PyTorch, presenting four typical deep learning case studies on image classification, object detection, semantic segmentation, and image captioning.

This book provides a short introduction and easy-to-follow implementation steps of deep learning using Google Cloud Platform. It also includes a practical case study that highlights the utilization of Python and related libraries for running a pre-trained deep learning model. In recent years, deep learning-based modeling approaches have been used in a wide variety of engineering domains, such as autonomous cars, intelligent robotics, computer...

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