Decision Trees, Random Forests, AdaBoost & XGBoost in R
Decision Trees and Ensembling techniques in R studio. Bagging, Random Forest, GBM, AdaBoost & XGBoost in R programming
Lectures -34
Resources -1
Duration -3.5 hours
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Course 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:
Identify the business problem which can be solved using Decision tree/ Random Forest/ XGBoost of Machine Learning.
Have a clear understanding of Advanced Decision tree based algorithms such as Random Forest, Bagging, AdaBoost and XGBoost
Create a tree based (Decision tree, Random Forest, Bagging, AdaBoost and XGBoost) model in R and analyze its result.
Confidently practice, discuss and understand Machine Learning concepts
How this course will help you?
A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning advanced course.
If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the advanced technique of machine learning, which are Decision tree, Random Forest, Bagging, AdaBoost and XGBoost.
Why should you choose this course?
This course covers all the steps that one should take while solving a business problem through Decision tree.
Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business.
What makes us qualified to teach you?
The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course.
Our Promise
Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.
Who this course is for:
- 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
Goals
- 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
Prerequisites
- Students will need to install R Studio software but we have a separate lecture to help you install the same
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Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
1 Lectures
-
Welcome to the Course! 03:07 03:07
Setting up R Studio and R Crash Course
9 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Machine Learning Basics
2 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Simple Decision trees
9 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Simple Classification Tree
4 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Ensemble technique 1 - Bagging
2 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Ensemble technique 2 - Random Forest
2 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Ensemble technique 3 - Boosting
4 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Instructor Details
![Abhishek and Pukhraj](https://www.tutorialspoint.com/assets/profiles/144265/profile/200_108665-1625290503.jpg)
Abhishek and Pukhraj
Course Certificate
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