About the project
A machine learning project that classifies network security events into three attack types — DDoS, Malware and Intrusion — using the Cyber Security Attacks dataset from Kaggle. The primary model is a Random Forest; Gradient Boosting and k-NN are trained alongside it for comparison. A Streamlit dashboard walks through exploratory analysis, preprocessing, model design, comparison and evaluation.
What it demonstrates
- Balanced three-class target
- Automatic data acquisition
- Full EDA suite
- Documented preprocessing
- Three models compared
Stack
- Python
- scikit-learn
- pandas
- Streamlit
- Kaggle
