This course is focusing on explaining ensemble methods. It will start with an introduction to machine learning and some important concepts. Next, the Decision tree model will be explained. Then, the students will know how an ensemble works, why it is important, and how to use it. Finally, some famous ensemble models will be introduced such as random-forest, Xgboost, Adaboost.
Objective
- Know the idea behind ensemble learning
- The advantages and the disadvantages of ensemble learning
- Understand how Random forest, Xgboost, Adaboost works
- Know how to train, test, and evaluate them
- Application of ensemble methods to solve real-world problems