Add comprehensive 15-day internship report for Risk Scoring Application project

[Copilot]

This PR adds a detailed 15-day internship report (15_GUNLUK_STAJ_RAPORU.md) documenting the development journey of the Risk Scoring Application with Deep Learning project.

What's Added

📋 Comprehensive Internship Report: A day-by-day breakdown covering:

• Days 1-5: Project setup, mock data generation, risk scoring algorithms, TensorFlow model development, and Streamlit web interface
• Days 6-10: Model optimization, data visualization, API development, testing infrastructure, and Docker containerization
• Days 11-15: Database integration, monitoring systems, MLOps implementation, security features, and documentation

🛠️ Technical Highlights Covered:

• Deep learning model development with TensorFlow/Keras
• Risk scoring algorithm implementation using statistical and rule-based approaches
• Interactive web application with Streamlit
• RESTful API development and authentication
• MongoDB integration for data persistence
• MLOps practices including model versioning and automated retraining
• Comprehensive testing and CI/CD pipeline setup
• Security implementation with JWT authentication and RBAC

📚 Learning Outcomes: Each day includes:

• Technical challenges encountered and solutions implemented
• Key learnings and insights gained
• Best practices discovered during development

🔧 Project Maintenance:

• Added .gitignore to exclude Python cache files and build artifacts
• Cleaned up repository by removing __pycache__ directories from version control

The report follows a structured format documenting real technical work that could be performed on this risk scoring application, providing valuable insights into modern software development practices, machine learning workflows, and production system design.

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