For those who’re seeking to elevate your MLOps initiatives to the subsequent degree, understanding its ideas is a necessary a part of the method. On this article, we’ll supply an introduction to MLOps ideas and elucidate the important thing ideas in an accessible method. Every precept will obtain a devoted tutorial with sensible examples in forthcoming articles. You’ll be able to entry all of the examples on my Github profile. Nevertheless, in the event you’re new to MLOps, I like to recommend beginning with my beginner-friendly tutorial to rise up to hurry. So let’s dive in!
Desk of contents:
· 1. Introduction
· 2. MLOps ideas
· 3. Versioning
· 4. Testing
· 5. Automation
· 6. Monitoring and monitoring
· 7. Reproducibility
· 8. Conclusion
My MLOps tutorials:
[I will be updating this list as I publish articles on the subject]
In a earlier article, we outlined MLOps as a set of methods and practices used to design, construct, and deploy machine studying fashions in an environment friendly, optimized, and arranged method. One of many key steps in MLOps is to determine a workflow and keep it over time.
The MLOps workflow outlines the steps to observe as a way to develop, deploy, and keep machine studying fashions. It contains the enterprise downside that describes the issue in a structured manner, information engineering that entails all the info preparation and preprocessing, machine studying mannequin engineering that entails all of the mannequin processing from designing the mannequin to its analysis, and code engineering that entails serving the mannequin. You’ll be able to check with the earlier tutorial in order for you extra particulars.