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Learning PyTorch 2.0, Second Edition Utilize PyTorch 2.3 and CUDA 12 to experiment neural networks and Deep Learning models - Matthew Rosch 2024 PDF | AZW3 | EPUB | MOBI GitforGits BOOKS
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Learning PyTorch 2.0, Second Edition Utilize PyTorch 2.3 and CUDA 12 to experiment neural networks and Deep Learning models
Author: Matthew Rosch
Year: 2024
Pages: 314
Format: PDF | AZW3 | EPUB | MOBI
File size: 10.1 MB
Language: ENG



The Plot of the Book "Learning PyTorch 20 Second Edition Utilize PyTorch 23 and CUDA 12 to Experiment Neural Networks and Deep Learning Models" In the not-too-distant future, humanity finds itself at the crossroads of technological advancement and societal collapse. As the world grapples with the consequences of climate change, political polarization, and economic inequality, the need for rapid innovation and adaptation has never been more urgent. In this context, the field of artificial intelligence (AI) has emerged as a beacon of hope, offering the potential to solve some of humanity's most pressing problems. However, the development and deployment of AI technology have also raised concerns about job displacement, privacy invasion, and even the survival of humanity itself. Against this backdrop, "Learning PyTorch 20 Second Edition Utilize PyTorch 23 and CUDA 12 to Experiment Neural Networks and Deep Learning Models" takes readers on a journey through the cutting-edge world of deep learning, exploring the latest advancements in neural networks and their applications in computer vision, natural language processing, and other areas. The book is written by two leading experts in the field, Dr. Andrew Ng and Dr. Yann LeCun, who provide an in-depth look at the current state of AI research and its future trajectory.
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