Automatic Training, Testing, and Deployment of AI Using MLOps: Overview

Sergio Virahonda

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3 May 2021CPOL4 min read

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In this article series, we'll demonstrate how to take use a CI/CD pipeline - a tool usually used by developers and DevOps teams - and demonstrate how to use it to create a complete training, test, and deployment pipeline for AI that meets the requirements of level 2 in the Google MLOps Maturity

Here we briefly explain CI/CD in the context of Machine Learning (ML).

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This article is part of the series 'Automatic Training, Testing, and Deployment of AI using CI/CD View All Next ▷

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

Written By

Sergio Virahonda

United States

Sergio Virahonda grew up in Venezuela where obtained a bachelor's degree in Telecommunications Engineering. He moved abroad 4 years ago and since then has been focused on building meaningful data science career. He's currently living in Argentina writing code as a freelance developer.

Automatic Training, Testing, and Deployment of AI Using MLOps: Overview

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