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⚙️ CI/CD for Machine Learning: GitHub Actions Pipeline

A 3D animated GitHub Actions-style pipeline: watch a commit flow through lint, automated tests, container build and deployment gates, and see how test failure rate and parallel jobs change the outcome.

AI & Machine Learning3DAdvanced60 FPS

A commit token travels through a glowing GitHub Actions-style pipeline — lint, tests, container build and production deploy — lighting up each stage as it runs and turning red or green depending on the outcome.

🔬 What It Demonstrates

How an ML repository's CI/CD workflow chains automated jobs so every push is linted, tested, packaged into a container image and deployed only if every gate before it passed — with no manual steps in between.

🎮 How to Use

Push a commit to trigger a run, tune the test failure rate to see gated failures block deployment, and toggle parallel jobs to compare fan-out speed against a strictly sequential workflow.

💡 Did You Know?

GitHub Actions can fan a single workflow out into dozens of parallel jobs across a build matrix — running the same test suite against multiple Python or CUDA versions simultaneously.

⚙ Under the hood

machine learninggithub actionsci cdautomationpipelinedeploymentThree.js

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install