Developed an AI-powered diabetes prediction application designed to analyze health-related input data and estimate diabetes risk using machine learning.

The project involved data preprocessing, exploratory data analysis, feature preparation, model training, evaluation, and integration of the trained model into an interactive application. The system allows users to enter relevant health indicators and receive a prediction through a simple, user-friendly interface.

One of the main challenges was transforming raw health data into a format suitable for machine learning while maintaining reliable model performance. I addressed this through data cleaning, preprocessing, feature analysis, model evaluation, and API-based integration.

The application combines machine learning with a practical user interface, demonstrating the complete workflow from data preparation to model deployment and prediction.

Technologies used include Python, Pandas, NumPy, Scikit-learn, FastAPI, and Streamlit.

Developed an interactive web platform for a private birthday event to simplify guest management and create an engaging digital experience.

The project included a QR-based guest entry system, guest search and identification, automatic attendance tracking, table information, photo sharing, and an interactive event gallery.

One of the main challenges was creating a simple experience for guests while allowing the administrator to manage guest records, track attendance in real time, and organize uploaded photos. I designed the application with a clean and user-friendly interface and integrated Supabase for database management, authentication, and photo storage.

The project was built using React, Vite, JavaScript, Supabase, and responsive web design principles.

The result was a functional event management platform that combined guest registration, attendance tracking, and photo sharing into one web application.

The client needed an interactive dashboard to monitor supervisor performance, analyze key performance indicators (KPIs), and transform operational data into clear and actionable insights.

The main requirements were to clean and organize the available data, identify relevant performance metrics, create meaningful visualizations, and develop an interactive dashboard that would make it easier to monitor trends and compare performance.

One of the main challenges was transforming raw and sometimes inconsistent data into a structured format suitable for analysis. I handled data cleaning, transformation, KPI calculations, exploratory analysis, and dashboard development.

The final dashboard provided an interactive view of key performance indicators, allowing the client to explore performance trends, identify areas requiring attention, and make data-driven decisions more efficiently.

The project demonstrated practical skills in data analysis, data visualization, business intelligence, KPI r