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https://github.com/sayedgamal99/sayedgamal99


https://github.com/sayedgamal99/sayedgamal99

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## 🚀 About Me

```yaml
name: Sayed Gamal
location: Cairo, Egypt
current_role: AI Engineer @ Noursoft
education: Computer Engineering - Mansoura University
passion:
[
"Artificial Intelligence",
"Machine Learning",
"Problem Solving",
"Innovation",
]
current_focus:
["LLM Applications", "Computer Vision", "MLOps", "System Architecture"]
fun_fact: "I've solved 450+ coding problems and led teams of 200+ participants!"
```

I'm passionate about creating intelligent systems that make a real difference. With hands-on experience in AI and machine learning, I love turning complex problems into practical solutions. and I always start by understanding the problem deeply before building. This mindset helps me deliver results that truly matter.

---

## Featured Projects


DriveMate: Multi-Agent Voice Assistant
Flare Guard: Real-Time Smoke Fire Detection And Alert System

















DriveMate is a multilingual AI assistant with natural dialogue and personality profiling that adapts to user preferences. Designed for ADAS systems, it delivers personalized, context-aware voice interactions and leverages tool integrations to enable hands-free driving. With intelligent long term memory, it enhances user experience and safety by supporting seamless, voice-driven control.


Flare Guard uses real-time computer vision for instant fire and smoke detection with real-time alerts. Trained YOLOv11 on 10,000+ images, it provides fast, reliable early warnings for safety-critical environments via Telegram and WhatsApp.



The Parasiter: Microscopic Image Classification
Customer Churn Prediction Analytics

















The Parasiter leverages deep learning for accurate microscopic parasite classification, making expert diagnostics accessible. It classifies 15 parasite species, features a user-friendly interface, Docker deployment, and live Azure hosting.


This project enables banks to predict customer churn using an ensemble of XGBoost, LightGBM, and CatBoost, achieving 0.891 AUC. It includes a full ML pipeline, real-time Flask Web app, and Docker deployment for actionable business insights.



View All Projects

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## Technology


Python
Pandas
NumPy
Matplotlib
Seaborn
Scikit-Learn
OpenCV
YOLO


TensorFlow
PyTorch
Hugging Face
OpenAI
LangChain
LangGraph
LlamaIndex
SmolAgents


vLLM
Ollama
FastAPI
Flask
Streamlit
Gradio
Postman
n8n


Dify
Azure
Docker
PostgreSQL
SQLite
MongoDB
Qdrant
Git


GitHub
Linux
Jupyter
HTML5
CSS3
JavaScript

## 📈 GitHub Stats


GitHub Stats


GitHub Streak


Contribution Graph

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