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Machine Learning শেখার শুরুতে আমরা সাধারণত dataset নিই, model train করি, accuracy দেখি এবং hyperparameter tune করি। ভালো score এলে মনে হয়—কাজ শেষ। কিন্তু industry-তে দ্রুত বোঝা যায়, একটি ভালো Machine Learning model এবং একটি ভালো Machine Learning system এক জিনিস নয়।

Notebook-এ model 95% accuracy দিতে পারে, কিন্তু production-এ prediction দিতে দুই second সময় নিতে পারে। Training-এর feature real-time prediction-এর সময় না-ও পাওয়া যেতে পারে। Traffic বাড়লে database slow হতে পারে। Model service down হলে application-এর গুরুত্বপূর্ণ feature বন্ধ হতে পারে। আবার model এক মাস পরও আগের মতো কাজ করছে কি না—সেটিও track করতে হয়।

এই জায়গা থেকেই শুরু হয় ML System Design & Production Engineering। Production-এ প্রশ্ন শুধু “কোন model ব্যবহার করব?” নয়। প্রশ্ন হলো—model-টিকে কীভাবে fast, scalable, reliable এবং useful service হিসেবে চালানো হবে?

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