[Udemy] Decision Trees, Random Forests, Bagging & XGBoost: R Studio
What you’ll learn
Strong understanding of determination bushes, bagging, Random Forest and Boosting methods in R studio
Perceive the enterprise situations the place determination tree fashions are relevant
Tune determination tree mannequin’s hyperparameters and consider its efficiency.
Use determination bushes to make predictions
Use R programming language to control knowledge and make statistical computations.
Implementation of Gradient Boosting, AdaBoost and XGBoost in R programming language
College students might want to set up R Studio software program however we’ve a separate lecture that will help you set up the identical
You are on the lookout for an entire Choice tree course that teaches you every thing it’s essential to create a Choice tree/ Random Forest/ XGBoost mannequin in R, proper?
You have discovered the proper Choice Bushes and tree based mostly superior methods course!
After finishing this course it is possible for you to to:
- Establish the enterprise drawback which will be solved utilizing Choice tree/ Random Forest/ XGBoost of Machine Studying.
- Have a transparent understanding of Superior Choice tree based mostly algorithms akin to Random Forest, Bagging, AdaBoost and XGBoost
- Create a tree based mostly (Choice tree, Random Forest, Bagging, AdaBoost and XGBoost) mannequin in R and analyze its outcome.
- Confidently apply, focus on and perceive Machine Studying ideas
Who this course is for:
- Individuals pursuing a profession in knowledge science
- Working Professionals starting their Knowledge journey
- Statisticians needing extra sensible expertise
- Anybody curious to grasp Choice Tree method from Newbie to Superior briefly span of time