Yuan tang (Oltre 2500 risultati)

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No Binding. Condizione: Very Good. ORIGINAL Article, disbound from journal; no covers; in very good condition. Journal.

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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.…

Paperback. Condizione: New. Selections from Classical Chinese: Historical Texts aims to instruct, inform, and inspire students of Chinese by presenting selected historical texts and their annotations. Taken from the seminal works known as the Four Histories, the fourteen included texts offer insights into the political, social, economic, and cultural aspects of China over a long period of time. The comprehensive annotations provide full pronunciation in pinyin, the grammatical function of individual words, and a full explication of the texts. One of the supplementary readings to Classical Chinese: A Basic Reader, this volume includes eight selections from the Shi Ji and two each from the Han Shu, the Hou Han Shu, and the San Guo Zhi. Each unfolds a fascinating account of the historical events and figures that represent certain salient values or distinctive cultural characteristics of what has come to be the Chinese tradition. The Shi Ji, a grand history by Sima Qian chronicling three thousand years of Chinese history, is divided into five sections of 130 chapters. Sima Qian is especially noted for his biographical style, and his work is considered the first and only "universal history" of China.The Han Shu, by Ban Gu, recounts the history of a single dynasty and is known for its dynastic style in depicting history. Together, these two histories represent paradigms of Chinese historiography. The Hou Han Shu, by Fan Ye, and the San Guo Zhi, by Chen Shou, continue this tradition of excellence. These four works are known collectively as the Four Histories. All texts are fully annotated to include a pinyin version marking the pronunciation of each word, glosses of each word by grammatical function and its meaning in the text, as well as detailed explication of each word. The exercises at the end of each selection are intended to help students apply newly gained knowledge, better appreciate Chinese history, and stimulate interest in additional reading.…

paperback. Condizione: New. Language:Chinese.Pages Number: 119 Publisher: Jilin Photography Pub. Date :2007-01-01 version 1. Contents: I play I play the rational enjoyment of playing the next Fun IQ.

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