Practical MLOps: Operationalizing Machine Learning Models

By:

Gift, Noah

By:

Deza, Alfredo

Publication details: Mumbai: Shroff Publishers & Distributors Pvt. Ltd., 2021Description: 439ISBN:

9789355420374

Subject(s):

Machine Learning

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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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
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

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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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