Search results for ""Author Chi Wang""

This study analyzes the United States policies regarding China during the administration of President George W. Bush. Chi Wang examines the relationship between the United States and China from its tense origins to its current stability and shows that the China policy of the U.S. is ultimately based on pragmatic national interest that eventually overcomes short-term ideological difficulties or mistakes by inexperienced American administrations. Briefly touching on the China-policy legacy of Presidents George H.W. Bush and Bill Clinton, Wang provides a review of significant developments in U.S.-China policy during President George W. Bush's first term in office. By following with an analysis of the varied agendas of Bush's foreign policy advisors during his second term, readers are able to trace the influence of advisors on the president's China policy. Wang chronicles the reordering of U.S. security priorities after September 11, showing how this prompted Washington to embrace China in a measured partnership and has resulted in the short-term stabilization of U.S.-China relations.

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Design systems optimized for deep learning models. Written for software engineers, this book teaches you how to implement a maintainable platform for developing deep learning models. In Engineering Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the deep learning development cycle Automate training for models in TensorFlow and PyTorch Optimize dataset management, training, model serving and hyperparameter tuning Pick the right open-source project for your platform Engineering Deep Learning Systems is a practical guide for software engineers and data scientists who are designing and building platforms for deep learning. It's full of hands-on examples that will help you transfer your software development skills to implementing deep learning platforms. You'll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting—and lucrative—career as a deep learning engineer. about the technology Behind every deep learning researcher is a team of engineers bringing their models to production. To build these systems, you need to understand how a deep learning system's platform differs from other distributed systems. By mastering the core ideas in this book, you'll be able to support deep learning systems in a way that's fast, repeatable, and reliable.

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