Continuous Integration / Continuous Deployment (CI/CD)


CI/CD bridges the gaps between development and operation activities and teams by enforcing automation in building, testing and deployment of applications. Modern day DevOps practices involve continuous development, continuous testing, continuous integration, continuous deployment and continuous monitoring of software applications throughout its development life cycle. The CI/CD practice or CI/CD pipeline forms the backbone of modern day DevOps operations.

Tutorials

Continuous Machine Learning (CML)
CML helps to organize MLOps infrastructure on top of the traditional software engineering stack instead of creating separate AI platforms.
ci-cd github-actions mlops production
GitHub Actions & Machine Learning Workflows with Hamel Husain
In this talk, Hamel will provide a brief tutorial on GitHub Actions, and will show you how you can use this new tool to automate your ML workflows.
github-actions machine-learning workflows video
Using GitHub Actions for MLOps & Data Science
A collection of resources on how to facilitate Machine Learning Ops with GitHub.
github ml-ops production github-actions
How to Set Up Continuous Integration for Machine Learning
How to Set Up Continuous Integration for Machine Learning with Github Actions and Neptune: Step by Step Guide.
ci-cd deep-learning experiment-tracking code
Machine Learning Pipelines for Kubeflow.
Kubeflow pipelines are reusable end-to-end ML workflows built using the Kubeflow Pipelines SDK.
kuberflow pipelines ci-cd production

Libraries

General
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