August 2025
Intermediate to advanced
276 pages
6h 16m
English
Content preview from Hands-On MLOps on Azure
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1
Understanding DevOps to MLOps
In the dynamic intersection of technology and innovation, the disciplines of DevOps and Machine Learning Operations (MLOps), represent transformative approaches to software and ML lifecycle management, respectively. This chapter explores how DevOps, a set of practices for faster software development, lays the groundwork for MLOps. MLOps is a similar approach specifically designed for the unique challenges of building and managing ML models.
Through a detailed exploration, we will uncover how the core principles of DevOps are not only applicable but essential to the effective management of ML processes. Because ML models can change their output for the same data, MLOps uses continuous monitoring, version control, ...
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