Aim:
To develop a predictive model for early detection of childhood malnutrition using survey-based health and nutrition data, and to compare the performance of ensemble and classical machine learning algorithms.
Aim:
To enhance DDoS attack detection by implementing a machine learning system with hyperparameter optimization and advanced prediction techniques, utilizing the CICIDS dataset to achieve high classification accuracy and improve network security.
Ā Ā Ā Ā Ā To develop a four-class disaster prediction system that uses SMOTE for class balancing, evaluates four advanced machine learning models, selects the best-performing classifier, and deploys it through an interactive web interface
To enhance DDoS attack detection by implementing a machine learning system with hyperparameter optimization and advanced prediction techniques, utilizing the CICIDS dataset to achieve high classification accuracy and improve network security.