What is Deployment?Deployment kya hai?

🧸 Think of it likeAise samjho

Like moving a dish from your home kitchen to a restaurant menu: now real customers can order it any time.Jaise ek dish ko ghar ki kitchen se restaurant ke menu pe laana: ab asli customers kabhi bhi order kar sakte hain.

📘 ExplainedVistaar se

Deployment packages the model with its preprocessing (often in Docker), serves it behind an API or runs it in batches, and adds monitoring, scaling and rollback. Safe rollouts use shadow mode or canaries. Most of the real effort in AI projects happens here, after the notebook.Deployment model ko uske preprocessing ke saath pack karta hai (aksar Docker mein), API ke peeche serve karta ya batches mein chalata hai, aur monitoring, scaling aur rollback jodta hai. Safe rollouts shadow mode ya canaries use karte hain. AI projects ki zyaadatar asli mehnat notebook ke baad yahin hoti hai.

💡 Real exampleAsli example

Wrapping a fraud model in FastAPI, packaging it with Docker and running it on Kubernetes.Fraud model ko FastAPI mein wrap karna, Docker se pack karna aur Kubernetes pe chalana.

📖 Learn it step by stepStep by step seekho

• Serving a model as an API with FastAPIModel ko FastAPI se API ke roop mein serve karna
• Docker: packaging your app so it runs anywhereDocker: app ko pack karna taaki kahin bhi chale
• Training vs inference: how ML runs in productionTraining vs inference: ML production mein kaise chalta hai

🔗 Related termsJude hue shabd

• InferenceUsing a trained model to make predictions on new data.Trained model se naye data pe predictions karna.
• DockerA tool that packages an app with everything it needs so it runs the same everywhere.Tool jo app ko uski har zaroori cheez ke saath pack karta hai taaki har jagah ek jaisa chale.
• 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.