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Learn MoreThis course describes tree-based algorithms for regression and classification. These methods are simple, intuitive and, more importantly, highly "visual". A deeper understanding of tree-based models provides a successful tool to comprehend advanced machine learning algorithms. By the end of this course, you will learn how to build a decision tree and understand their advantages and limitations.
Instructor for this course
Kristin Day
Course Introduction
Initial Vocabulary
Decision Tree Pros and Cons
Decision Tree Classification Intro
Types of Decision Trees
Model Selection
Feature Engineering
Measures of Impurity - Gini
Measures of Impurity - Entropy
Model Tuning - Part 1
Model Tuning - Part 2
Model Pre-pruning
Model Post-pruning
Visualizing and Explaining Results
Mushroom Classification
Decision Tree Regression Intro
Tuning Regression Models
Pruning Regression Models
Boston House Prices Regression
Visualizing the Boston Regression Tree
Course Conclusion
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