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MLOps Engineering at Scale 可以在 Hong Kong 在線購物嗎？

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物品 #: 38043469

MLOps Engineering at Scale

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物品 #: 38043469

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產品詳情

Dodge costly and time-consuming infrastructure tasks, and rapidly bring your machine learning models to production with MLOps and pre-built serverless tools!In MLOps Engineering at Scale you will learn:Extracting, transforming, and loading datasetsQuerying datasets with SQLUnderstanding automatic differentiation in PyTorchDeploying model training pipelines as a service endpointMonitoring and managing your pipeline’s life cycleMeasuring performance improvementsMLOps Engineering at Scale shows you how to put machine learning into production efficiently by using pre-built services from AWS and other cloud vendors. You’ll learn how to rapidly create flexible and scalable machine learning systems without laboring over time-consuming operational tasks or taking on the costly overhead of physical hardware. Following a real-world use case for calculating taxi fares, you will engineer an MLOps pipeline for a PyTorch model using AWS server-less capabilities.About the technologyA production-ready machine learning system includes efficient data pipelines, integrated monitoring, and means to scale up and down based on demand. Using cloud-based services to implement ML infrastructure reduces development time and lowers hosting costs. Serverless MLOps eliminates the need to build and maintain custom infrastructure, so you can concentrate on your data, models, and algorithms.About the bookMLOps Engineering at Scale teaches you how to implement efficient machine learning systems using pre-built services from AWS and other cloud vendors. This easy-to-follow book guides you step-by-step as you set up your serverless ML infrastructure, even if you’ve never used a cloud platform before. You’ll also explore tools like PyTorch Lightning, Optuna, and MLFlow that make it easy to build pipelines and scale your deep learning models in production.What's insideReduce or eliminate ML infrastructure managementLearn state-of-the-art MLOps tools like PyTorch Lightning and MLFlowDeploy training pipelines as a service endpointMonitor and manage your pipeline’s life cycleMeasure performance improvementsAbout the readerReaders need to know Python, SQL, and the basics of machine learning. No cloud experience required.About the authorCarl Osipov implemented his first neural net in 2000 and has worked on deep learning and machine learning at Google and IBM.Table of ContentsPART 1 - MASTERING THE DATA SET1 Introduction to serverless machine learning2 Getting started with the data set3 Exploring and preparing the data set4 More exploratory data analysis and data preparationPART 2 - PYTORCH FOR SERVERLESS MACHINE LEARNING5 Introducing PyTorch: Tensor basics6 Core PyTorch: Autograd, optimizers, and utilities7 Serverless machine learning at scale8 Scaling out with distributed trainingPART 3 - SERVERLESS MACHINE LEARNING PIPELINE9 Feature selection10 Adopting PyTorch Lightning11 Hyperparameter optimization12 Machine learning pipeline

Publisher	Manning
Publication date	March 1, 2022
Language	English
Print length	344 pages
ISBN-10	1617297763
ISBN-13	978-1617297762
Item Weight	1.25 pounds (570 grams)
Dimensions	7.38 x 0.7 x 9.25 inches (18.7 x 1.8 x 23.5 cm)

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MLOps Engineering at Scale

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題: 如何從 Ubuy 在線購物 MLOps Engineering at Scale？

回答: 從 Ubuy 在線購物 MLOps Engineering at Scale 非常簡單。. 您只需搜索產品，在結賬時選擇運輸方式，然後將其運送到您所在的位置。
題: MLOps Engineering at Scale 可以在 Hong Kong 在線購物嗎？

回答: 是的，您可以在 Ubuy Hong Kong 以合理的價格購買該產品。. MLOps Engineering at Scale 在本地不可用，但您可以信任我們的快遞服務。
題: 下訂單後需要多長時間才能收到產品？

回答: 您訂購的產品的交貨時間根據您訂購的商品和您選擇的運輸方式而有所不同。. 結賬時會提到預計送貨時間，所以購物時請放心。

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HKD 528

現在訂購，約可在下列時間收貨：星期六, 十月 10

QTY:

存貨僅剩 3 個物品。

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MLOps Engineering at Scale