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Hyperparameter Tuning in Tree-Based Models
This course is designed to help the learners understand various hyperparameters used in tree-based models such as decision tree to solve regression and classification problems and its implementation in real-world business cases.
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2 Videos
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6 Data Cases
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2 Readings
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4 Quizzes
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Difficulty: Advanced
Prior knowledge or professional experience is strongly recommended.
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Duration: Approximately 12 hours
Course Overview
- Tree-based models are one of the most widely used algorithms in the realm of machine learning and data science.
- Tree-based models have multiple hyperparameters and choosing their values optimally can lead to significant improvement in model performance.
- Learn the working of the decision tree algorithm and how different hyperparameters can be implemented to boost model performance.
- Gain practical experience by applying the understanding in 4 real-world business case scenarios.
What’s included
Flexible Scheduling
Start learning online immediately, at your own pace
Desktop Only
We recommend completing this project on a desktop
Skills You Will Learn
Associated Learning Tracks
How it Works
Learn new skills that will boost your career by enrolling in courses across data analytics, data science, ML and AI. These courses will utilize readings, videos, quizzes, data cases, and even coding exercises to teach you skills and concepts in a way that will solidify your new knowledge for hands-on application.
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.
Complete assessments and track your progress in real-time to benchmark your proficiency in relation to key functional areas. As you progress through your courses, our patented platform will utilize ML and AI to record and analyze your inputs and output to provide active feedback and recommendations that will help you learn more effectively than the standard Letter Grade system used today.
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Rolai’s patented process provides a personalized learning process for each user. Rolai goes deeper than simply learning concepts and testing your skills. At Rolai, learners can apply their skills to actual industry use cases and projects.
Our courses include readings, videos, quizzes, and hands-on data cases that are completed using our virtual lab; give learners an applied learning experience.
No additional tools are needed to begin learning with Rolai. Our virtual lab contains the necessary data workspace and an embedded coding console.
- We have internal SMEs across industries and domains that we work with to develop relevant content and assure quality datasets and problem statements.
- We also work with enterprises and universities to develop new content directed towards their industry and expertise.
