Operationalizing Machine Learning Pipelines : Building Reusable and Reproducible Machine Learning Pipelines Using MLOps / Vishwajyoti Pandey & Shaleen Bengani.

By:

Pandey, Vishwajyoti [author.]

Contributor(s):

Bengani, Shaleen [author.]

Material type: Text

TextPublisher: New Delhi : BPB Publications, 2022Edition: first editionDescription: 162 pages : illustrations ; 23 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9789355510235

Subject(s):

DDC classification:

23 005.4 P.V.O

Contents:

DS/ML Projects – Initial Setup; ML Projects Lifecycle; ML Architecture – Framework & Components; Data Exploration & Problem Quantification; Training & Testing ML Models; Model Performance Measurement; CRUD with JS Frameworks; Feature Store; Building ML Pipeline.

Summary: A practitioner’s guide to implementing end-to-end MLOps workflows. Covers features such as GitOps automation, feature store creation, serverless pipelines, model serving with KFServing and Polyaxon, and model monitoring in production—ideal for ML engineers, data scientists, and DevOps professionals.turn0search3turn0search12

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode	Item holds
Books	Media and mass communication Library B2	005.4 P.V.O	C.1	Available		MA0002223

Total holds: 0

Includes practical case studies, tool examples, and key feature highlights.

A practitioner’s guide to implementing end-to-end MLOps workflows. Covers features such as GitOps automation, feature store creation, serverless pipelines, model serving with KFServing and Polyaxon, and model monitoring in production—ideal for ML engineers, data scientists, and DevOps professionals.turn0search3turn0search12

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