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Udemy - Decision Trees, Random Forests, AdaBoost & XGBoost In R
TORRENT SUMMARY
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Solid understanding of decision trees, bagging, Random Forest and Boosting techniques in R studio
Understand the business scenarios where decision tree models are applicable
Tune decision tree model's hyperparameters and evaluate its performance.
Use decision trees to make predictions
Use R programming language to manipulate data and make statistical computations.
Implementation of Gradient Boosting, AdaBoost and XGBoost in R programming language
Requirements
Students will need to install R Studio software but we have a separate lecture to help you install the same
Description
You're looking for a complete Decision tree course that teaches you everything you need to create a Decision tree/ Random Forest/ XGBoost model in R, right?
You've found the right Decision Trees and tree based advanced techniques course!
After completing this course you will be able to:
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[ FreeCourseWeb.com ] Udemy - Decision Trees, Random Forests, AdaBoost & XGBoost in R.zip
