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Decision Tree - Theory, Application and Modeling using R
Analytics/ Supervised Machine Learning/ Data Science: CHAID / CART / Random Forest etc. workout (Python demo at the end)
This Course Includes
udemy
4.8 (298 reviews )
8 total hours 
english
Online - Self Paced
course
Udemy
About Decision Tree - Theory, Application and Modeling using R
What is this course?
Decision Tree Model building is one of the most applied technique in analytics vertical. The decision tree model is quick to develop and easy to understand. The technique is simple to learn. A number of business scenarios in lending business / telecom / automobile etc. require decision tree model building.
This course ensures that student get understanding of
Course Tags
Material in this course
How long the course should take?
It should take approximately 8 hours to internalize the concepts and become comfortable with the decision tree modeling using R
The structure of the course
Section 1 – motivation and basic understanding
Section 2 – practical (for categorical output)
Section 3 – Algorithm behind decision tree
Section 4 – Other algorithm for decision tree
Why take this course?
Take this course to
What You Will Learn?
- Get Crystal clear understanding of decision tree.
- Understand the business scenarios where decision tree is applicable.
- Become comfortable to develop decision tree using R statistical package.
- Understand the algorithm behind decision tree i.e. how does decision tree software work.
- Understand the practical way of validation, auto validation and implementation of decision tree.