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Basics of Hyperparameter Tuning
This course will allow learners to understand the concept of hyperparameter tuning for both regression and classification models that can help in improving the overall model performance, along with their hands-on application 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
- Linear and Logistic regression are one of the most widely used algorithms in the realm of machine learning and data science.
- Models can have a number of hyperparameters which can significantly affect the performance based on how optimally the values are chosen.
- Learn all the steps required to optimize these algorithms for performance improvement through hyperparameter tuning.
- Gain practical experience by apply the understanding in 6 real-world based business 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
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