Decision Trees, Random Forests, AdaBoost & XGBoost in R | Programming Buddy Club | Free Udemy Courses

DECISION TREES AND ENSEMBLING TECHINQUES IN R STUDIO. BAGGING, RANDOM FOREST, GBM, ADABOOST & XGBOOST IN R PROGRAMMING

Discount - $  FREE 100% Off

• Lectures - 53 lectures
• Skill Level -Beginner Level
• Language -  English
• Published -  Last updated 1/2020
• Coupon -JANFREE2020
• Rating -
• Students Enrolled -

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Course Includes

• ☑️ 6 hours on-demand video

• ☑️ 3 articles

• ☑️ 16 downloadable resources

• ☑️ Full lifetime access

• ☑️ Access on mobile and TV

• ☑️ Certificate of Completion

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What Will I learn?

• ☑️ 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

Who is the target audience?

• ☑️ People pursuing a career in data science

• ☑️ Working Professionals beginning their Data journey

• ☑️ Statisticians needing more practical experience

• ☑️ Anyone curious to master Decision Tree technique from Beginner to Advanced in short span of time

Take this course!

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