You're reading from Engineering MLOps

Product typeBook

Published inApr 2021

PublisherPackt

ISBN-139781800562882

Edition1st Edition

Tools

Azure Functions

Concepts

Machine Learning

Author (1)

Emmanuel Raj

Summary

In this chapter, we have learned the key principles of continuous operations in MLOps, primarily, continuous integration, delivery, and deployment. We have learned this by performing a hands-on implementation of setting up a CI/CD pipeline and test environment using Azure DevOps. We have tested the pipeline for execution robustness and finally looked into some triggers to enhance the functionality of the pipeline and also set up a Git trigger for the test environment. This chapter serves as the foundation for continual operations in MLOps and equips you with the skills to automate the deployment pipelines of ML models for any given scenario on the cloud, with continual learning abilities in tune with your business.

In the next chapter, we will look into APIs, microservices, and what they have to offer for MLOps-based solutions.

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Engineering MLOps

Published in: Apr 2021Publisher: PacktISBN-13: 9781800562882

Author (1)

Emmanuel Raj

Emmanuel Raj is a Finland-based Senior Machine Learning Engineer with 6+ years of industry experience. He is also a Machine Learning Engineer at TietoEvry and a Member of the European AI Alliance at the European Commission. He is passionate about democratizing AI and bringing research and academia to industry. He holds a Master of Engineering degree in Big Data Analytics from Arcada University of Applied Sciences. He has a keen interest in R&D in technologies such as Edge AI, Blockchain, NLP, MLOps and Robotics. He believes "the best way to learn is to teach", he is passionate about sharing and learning new technologies with others.
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