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ML Model එකක් AWS Cloud එකට දාමු! | How to Deploy a Full-Stack ML App on AWS EC2 with Docker Compose 🌿 මෙම වීඩියෝවෙන් අපි Docker Compose තාක්ෂණය සහ AWS EC2 Cloud සර්වර් එකක් භාවිතා කරලා, React Frontend එකක් සහ FastAPI Backend (Machine Learning Inference Engine) එකක් ලෝකේ කොහේ ඉන්න කෙනෙකුට වුණත් Live ඇක්සස් කරන්න පුළුවන් විදිහට සජීවීව ධාවනය කරවන ආකාරය (Live Deployment) මුල ඉඳන් සරලව කතා කරනවා. ඔයාගේ local පරිගණකයේ වැඩ කරන full-stack project එකක් 503, 404 හෝ Connection Refused වැටෙන්නේ නැතුව, public IP එකක් හරහා AWS cloud එක මත නිවැරදිව deploy කරද්දී එන පොදු ගැටළු රාශියක් අපි මේ වීඩියෝ එකේදී live troubleshooting කරලා විසඳනවා! 💻 Core Technology Stack Used: Frontend: React.js (Served via Production Nginx Server) Backend Engine: FastAPI (Python Machine Learning Application) Containerization: Docker & Docker Compose Cloud Infrastructure: AWS EC2 (Ubuntu Linux Instance) 🔗 Official Project Resources: GitHub Repository: https://github.com/kosalanayanajithde... Docker Hub Backend Image: https://hub.docker.com/r/kosala2002/c... Live Demo Public IP (Temporary): http://98.93.30.243 💬 Got Questions or Build Errors? ඔයාටත් Docker Build කරද්දී හෝ AWS එකේ Ports open කරද්දී ගැටළුවක් ආවොත් පල්ලෙහායින් Comment එකක් දාන්න. වීඩියෝ එක වටිනවා කියලා හිතුණොත් LIKE කරලා, SHARE කරලා, SUBSCRIBE වෙන්න අමතක කරන්න එපා! #MachineLearning Sinhala #AWS #Docker Sinhala #FastAPI #ReactJS #DataScience #AgriTech #DevOps Sinhala #CloudComputing #DockerCompose #WebDeployment #TechSinhala

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