August 2025
Intermediate to advanced
276 pages
6h 16m
English
Content preview from Hands-On MLOps on Azure
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3
Reproducible and Reusable ML
This chapter builds upon the concepts introduced in Chapter 2, focusing on automating the machine learning (ML) lifecycle for robust and efficient model development and deployments. Reproducibility and reusability are fundamental principles in ML to ensure the reliability and efficiency of your projects. Reproducibility allows you to recreate the same results consistently, which is essential for verifying experiments and building trust in your models. Reusability enables you to leverage existing components and workflows, saving time and resources while maintaining consistency across different projects.
This chapter delves into strategies for automating a typical ML workflow, with a strong emphasis on enhancing ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.