Network Latency Prediction

Project Overview

This project focuses on advanced regression techniques to predict network latency and introduces synthetic data generation for training robust models. We'll learn how to create realistic training data when real-world data is limited.

Key Learning Objectives

• Advanced regression techniques
• Synthetic data generation
• Feature engineering for network metrics
• Model validation with synthetic data
• Implementing ensemble methods

Technologies Used

• Python
• scikit-learn
• SDV (Synthetic Data Vault)
• XGBoost for regression
• pandas and numpy

Additional Resources

For detailed implementation guide, code examples, and step-by-step instructions, please visit the GitHub Project Repository.