BOOK

Efficient MLOps

Oketunji, Abiodun Finbarrs

Year: 2024 Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

Efficient MLOps is a detailed strategy for streamlining machine-learning operations through GitHub-centric workflows and automation. From setting up efficient training pipelines to implementing real-time model monitoring—this book presents battle-tested best practices for ML Engineers.Learn the art of continuous integration and deployment for machine-learning projects using GitHub Actions and modern MLOps tools. Learn practical techniques for data versioning, model serving, and maintaining high-performance ML systems in production. Transform your ML projects from experimental notebooks to production-ready systems with industry-standard practices and workflows.Whether you're a Data Scientist or ML Engineer, this book provides the knowledge to build and maintain scalable ML systems using GitHub's innovative ecosystem.

Keywords:
Workflow Software deployment Scalability Key (lock) Pipeline (software) Best practice

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Topics

Sulfur Compounds in Biology
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Biochemistry
Folate and B Vitamins Research
Health Sciences →  Medicine →  Rheumatology
Aldose Reductase and Taurine
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Cell Biology

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