Yuan tang (Oltre 2500 risultati)

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Paperback. Condizione: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

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Condizione: As New. Unread copy in mint condition.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: Sammlerstück - Wie neu.

Paperback. Condizione: new. Paperback. Brain-Based Learning and Education Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback. Condizione: New. Practical patterns for scaling machine learning from your laptop to a distributed cluster. In  Distributed Machine Learning Patterns you will learn how to: Apply distributed systems patterns to build scalable and reliable machine learning projectsConstruct machine learning pipelines with data ingestion, distributed training, model serving, and moreAutomate machine learning tasks with Kubernetes, TensorFlow, Kubeflow, and Argo WorkflowsMake trade offs between different patterns and approachesManage and monitor machine learning workloads at scale Scaling up models from standalone devices to large distributed clusters is one of the biggest challenges faced by modern machine learning practitioners. Distributed Machine Learning Patterns teaches you how to scale machine learning models from your laptop to large distributed clusters.  In Distributed Machine Learning Patterns, you'll learn how to apply established distributed systems patterns to machine learning projects, and explore new ML-specific patterns as well. Firmly rooted in the real world, this book demonstrates how to apply patterns using examples based in TensorFlow, Kubernetes, Kubeflow, and Argo Workflows. Real-world scenarios, hands-on projects, and clear, practical DevOps techniques let you easily launch, manage, and monitor cloud-native distributed machine learning pipelines Distributed Machine Learning Patterns teaches you how to scale machine learning models from your laptop to large distributed clusters. In it, you'll learn how to apply established distributed systems patterns to machine learning projects, and explore new ML-specific patterns as well. Firmly rooted in the real world, this book demonstrates how to apply patterns using examples based in TensorFlow, Kubernetes, Kubeflow, and Argo Workflows. Real-world scenarios, hands-on projects, and clear, practical DevOps techniques let you easily launch, manage, and monitor cloud-native distributed machine learning pipelines. about the technology Scaling up models from standalone devices to large distributed clusters is one of the biggest challenges faced by modern machine learning practitioners. Distributing machine learning systems allow developers to handle extremely large datasets across multiple clusters, take advantage of automation tools, and benefit from hardware accelerations. In this book, Kubeflow co-chair Yuan Tang shares patterns, techniques, and experience gained from years spent building and managing cutting-edge distributed machine learning infrastructure. about the book Distributed Machine Learning Patterns is filled with practical patterns for running machine learning systems on distributed Kubernetes clusters in the cloud. Each pattern is designed to help solve common challenges faced when building distributed machine learning systems, including supporting distributed model training, handling unexpected failures, and dynamic model serving traffic. Re.…

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Paperback. Condizione: New. This supplemental volume continues the rigorous standard set forth in the main, three-volume Classical Chinese: A Basic Reader while reinforcing its linguistic lessons from carefully chosen representative works. Comprised of three parts--"Poetry," "Lyrics," and "Prose"--it presents texts, chronologically, that represent the artistic embodiment of China's Confucian and Taoist thought. Two introductions separately describe the structural and formal features of regulated verse and parallel prose; each genre is unique to Chinese literature yet both share common characteristics tempered by the Chinese language. The main text and its four supplementary volumes together represent the most comprehensive and authoritative textbook on the language, literature, philosophy, history, and religion of premodern China. Field-tested and fine-tuned for years in classroom settings by three members of the Chinese Linguistics Project at Princeton University, it is the definitive new resource for students and instructors of classical Chinese language or culture.…