What is CI/CD?CI/CD kya hai?

🧸 Think of it likeAise samjho

Like a factory quality check on every product before it leaves: each change is tested automatically, and only good ones are shipped.Factory mein har product nikalne se pehle quality check jaisa: har badlaav automatically test hota hai, aur sirf sahi wale bheje jaate hain.

📘 ExplainedVistaar se

Continuous integration runs tests on every change; continuous delivery deploys passing changes safely. For ML, add data validation, a small training run, evaluation against a fixed set before promotion, and gradual rollouts with rollback. Tools include GitHub Actions, Jenkins and GitLab CI.Continuous integration har badlaav pe tests chalata hai; continuous delivery paas hue badlaav safely deploy karta hai. ML mein data validation, chhota training run, promotion se pehle fixed set pe evaluation, aur rollback ke saath dheere rollouts jodo. Tools: GitHub Actions, Jenkins aur GitLab CI.

💡 Real exampleAsli example

A pull request automatically runs unit tests and an eval suite before it can be merged.Pull request merge hone se pehle apne aap unit tests aur eval suite chalata hai.

📖 Learn it step by stepStep by step seekho

• MLOps: experiment tracking and model registriesMLOps: experiment tracking aur model registries
• Git and GitHub: saving and sharing your workGit aur GitHub: apna kaam save aur share karna

🔗 Related termsJude hue shabd

• MLOpsThe practices and tools for putting ML models into production and keeping them healthy.ML models ko production mein laane aur swasth rakhne ke tarike aur tools.
• Model registryA catalogue of trained model versions with their metrics and stage (testing, production).Trained model versions ka catalogue, unke metrics aur stage (testing, production) ke saath.
• EvalsA repeatable set of test cases and scoring rules that measures whether an AI system works well.Test cases aur scoring rules ka dohraaya ja sakne wala set jo naapta hai AI system acche se kaam karta hai ya nahi.