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Tree Models in Python
This course covers a detailed explanation of tree-based models and their application in both regression and classification tasks and their Python implementation on real-world business scenarios.
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1 Video
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1 Coding Case
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1 Reading
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1 Quiz
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Difficulty: Advanced
Prior education or professional experience required
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Duration: Approximately 6 hours
Course Overview
- Tree-based models are a family of supervised machine learning algorithms in Machine Learning that enable higher predictive power and better stability.
- Unlike the linear models, they can be used efficiently with non-linear data.
- Learn the fundamental concepts behind tree-based models, their advantages and how to build a robust model using Python for both regression and classification based tasks.
- Gain practical experience by applying the knowledge and coding skills on real-world based business scenarios.
What’s included
Flexible Scheduling
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Desktop Only
We recommend completing this project on a desktop
Skills you will learn
Associated Learning Tracks
How it Works
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With our hands-on projects, you will take your newly learned skills along with our 750+ low-code/no-code functions and embedded coding console to complete milestone-based projects. Once completed, you will have effectively applied new skills and concepts to real-world data cases that can be translated directly into your career.
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