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Practical MLOps: Operationalizing Machine Learning Models

By: By: Publication details: Mumbai: Shroff Publishers & Distributors Pvt. Ltd., 2021Description: 439ISBN:
  • 9789355420374
Subject(s): DDC classification:
  • 006.31 GIF
Summary: etting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models. Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack.
List(s) this item appears in: New Arrivals for the Month of September - 2023
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Item type Current library Collection Call number Status Date due Barcode Item holds
Book Book Alliance College of Engineering and Design CSE & IT 006.31 GIF (Browse shelf(Opens below)) Checked out 18/09/2024 E12300
Total holds: 0

etting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.

Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack.

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