PyTorch：用简便和灵活性构建AI模型

English | 2024 | ASIN: B0DK755MRP | 103 pages| Epub | 2 MB

Unlock the power of PyTorch, one of the most dynamic and flexible deep learning frameworks in the world of artificial intelligence. PyTorch: Building AI Models with Ease and Flexibility is a comprehensive guide that takes readers on a journey from the fundamentals of PyTorch to advanced applications in AI research and industry.Designed for AI enthusiasts, researchers, and professionals alike, this book offers a hands-on, practical approach to learning PyTorch. Starting with the basics of tensor operations and automatic differentiation, readers will quickly grasp how to build, train, and optimize deep learning models. Each chapter introduces progressively complex concepts, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and advanced techniques like transfer learning, GANs, and reinforcement learning.Whether you're working in computer vision, natural language processing, or large-scale distributed training, this book equips you with the tools and knowledge to master PyTorch. Learn how to efficiently handle large datasets, deploy models to mobile and cloud environments, and leverage the growing PyTorch ecosystem through libraries like PyTorch Lightning

解锁PyTorch的力量，这是人工智能领域中最动态和灵活的深度学习框架之一。《PyTorch：轻松构建AI模型与灵活性》是一本全面指南，带领读者从PyTorch的基础知识到人工智能研究和工业应用的高级应用之旅。这本书旨在面向所有人工智能爱好者、研究人员及专业人士，提供一种实践性的方法来学习PyTorch。从基本的张量操作和自动求导开始，读者可以迅速掌握如何构建、训练和优化深度学习模型。每章都逐步介绍更复杂的概念，包括卷积神经网络（CNN）、循环神经网络（RNN）以及像迁移学习、GANs 和强化学习等高级技术。无论你在计算机视觉、自然语言处理还是大规模分布式训练中工作，这本书都能提供你掌握PyTorch所需的工具和知识。学会如何高效地处理大数据集，将模型部署到移动和云环境，并通过如PyTorch Lightning这样的库来利用不断增长的PyTorch生态系统。

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