How I Built Production-Grade AI Systems While Still a Student

Nader Al Shawki, a final-year AI Engineering student at Al-Razi University in Yemen, has built several production-grade AI systems including a tomato leaf disease detection platform using YOLOv8 and FastAPI, a pneumonia detection system with PyTorch, and a face detection and emotion recognition system. He is currently learning LLMs, RAG, LangChain, and AI agents.

🚀 Hello, DEV Community I'm Nader Al Shawki , a final-year AI Engineering student at Al-Razi University, Yemen. This is my first post here, and I'm excited to start sharing my journey with this amazing community. 🎯 Who Am I? I'm passionate about building production-grade AI systems that solve real-world problems. My main areas of focus are: - 🖼️ Computer Vision & Deep Learning - 🤖 ML Model Deployment Docker, FastAPI, REST APIs - 🧠 LLMs, RAG, and AI Agents currently learning - 📊 Data Visualization & Analytics Power BI 💡 What I've Built So Far 1. 🍅 Tomato Leaf Disease Detection Platform - Tech: YOLOv8, PyTorch, FastAPI, Docker - What it does: Detects tomato leaf diseases from images with real-time inference. Containerized with Docker for easy deployment. 2. 🫁 Pneumonia Detection System - Tech: PyTorch, CNN Architecture, Medical Imaging - What it does: A deep learning model that detects pneumonia from chest X-ray images. 3. 📊 Sales Profit Analysis Dashboard - Tech: Power BI, DAX, Data Analysis - What it does: Interactive dashboard for tracking sales KPIs. 4. 😀 Face Detection & Emotion Recognition - Tech: OpenCV, Deep Learning - What it does: Real-time face detection, age estimation, emotion recognition, and gender classification. 5. 🍽️ Restaurant Website - Tech: HTML5, CSS3, JavaScript - What it does: Fully responsive restaurant website with interactive UI. 🌱 What I'm Currently Learning - LLMs Large Language Models - RAG Retrieval-Augmented Generation LangChain & AI Agents - Workflow automation with n8n 🔗 Let's Connect Thanks for reading I'll be posting regularly about AI projects, tutorials, and lessons learned. Stay tuned 🚀