Machine Learning with Python: Decision Trees

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Free Online Course: Machine Learning with Python: Decision Trees provided by LinkedIn Learning is a comprehensive online course, which lasts for 1-2 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from LinkedIn Learning. Machine Learning with Python: Decision Trees is taught by Frederick Nwanganga.

Overview
  • Learn how to build decision trees in Python to measure impurity within a partition and improve outcomes on machine learning projects.

Syllabus
  • Introduction

    • Making decisions with Python
    • What you should know
    • The tools you need
    • Using the exercise files
    1. Decision Trees
    • What is a decision tree?
    • How is a classification tree built?
    • How do classification trees measure impurity?
    • How is a regression tree built?
    • How to prune a decision tree
    • Why and when to use a decision tree
    2. Working with Classification Trees
    • How to build a classification tree in Python
    • How to visualize a classification tree in Python
    • How to prune a classification tree in Python
    3. Working with Regression Trees
    • How to build a regression tree in Python
    • How to visualize a regression tree in Python
    • How to prune a regression tree in Python
    Conclusion
    • Next steps with decision trees