One Day Workshop on Advanced Ensemble Learning Techniques for Supervised Machine Learning using Python 2026 - VIT Vellore

This workshop provides a forum for members of the research and academic community to understand recent technologies in ML foundations and ensemble techniques such as Boosting, Voting, and Stacking, along with their practical implementation using Python. The One-Day Workshop on Advanced Ensemble Learning Techniques for Supervised Machine Learning gives participants a comprehensive understanding of the fundamental concepts, advanced methodologies, and practical applications of ensemble learning. It introduces the principles of ensemble modeling and explains how combining multiple base learners can improve the accuracy and reliability of predictive models. Techniques covered: Bagging, Random Forest, Boosting, AdaBoost, Gradient Boosting, XGBoost, LightGBM, CatBoost, Voting Classifiers, and Stacking - with their theoretical foundations, strengths, limitations, and suitability for different supervised learning tasks. Participants will also learn model selection, hyperparameter tuning, feature importance analysis, and performance evaluation for classification and regression. A hands-on session using Python and Scikit-learn lets participants implement ensemble algorithms, experiment with real-world datasets, and compare individual models with ensemble approaches. Highlights - ML Foundations - Ensemble techniques: Boosting, Voting, Stacking - AdaBoost, Gradient Boosting, XGBoost and Random Forest - Practical implementation using Python Date & time: 25 November 2026, 9:45 AM - 4:50 PM Mode: Hybrid - online and offline at VIT University, Vellore Organizing department: Computer Science & Engineering / Information Technology Last date for registration: 23 November 2026 Registration fee (including GST) - Faculty members: Rs. 350 - Research scholars: Rs. 300 - UG/PG students: Rs. 250 Certificates provided for all participants. Register: https://events.vit.ac.in/Home/eventDetails/001240