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.
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
What you will learn
ACF Type: wysiwyg
The participants will learn Machine learning models with a real-world case study
The participants will get hands-on coding experience on Decision trees, Ensemble learning, and Random forest, xgboost and adaboost, etc.
They will be able to apply them with a real life case study