Efficient MLOps
Efficient MLOps by Finbarrs Oketunji
English | October 26, 2024 | ISBN: N/A | ASIN: B0DL4GDJ9Z | 501 pages | EPUB | 0.41 Mb
English | October 26, 2024 | ISBN: N/A | ASIN: B0DL4GDJ9Z | 501 pages | EPUB | 0.41 Mb
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.