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Model থেকে Production—সহজ বাংলায় Core Concepts, Trade-offs ও Interview Preparation
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।
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About the Book
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?
About the Author
Md. Aminul Haque Palash is a Software Engineer and Machine Learning practitioner. He holds a B.Sc. degree in Computer Science and Engineering (CSE) from Chittagong University of Engineering and Technology (CUET). His work focuses on building practical AI solutions by combining software engineering with machine learning.
One of his key areas of interest is making Machine Learning models effective and reliable in real-world production environments. He believes that the success of an ML system is not determined by model accuracy alone; scalability, latency, data quality, reliability, monitoring, and real-world business requirements are equally important.
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