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Polynomial Regression Techniques

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Track :

Mathematics

Lessons no : 25

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What will you learn in this course?
  • Master polynomial regression techniques for modeling non-linear relationships in data analysis and machine learning applications
  • Apply polynomial feature transformation to enhance predictive accuracy in regression models
  • Evaluate model performance using metrics like R-squared, RMSE, and adjusted R-squared for polynomial regression models
  • Implement polynomial regression in Python and R for real-world data analysis projects
  • Identify overfitting risks in polynomial models and apply regularization techniques to mitigate them
  • Use polynomial regression to analyze complex data patterns in finance, healthcare, and engineering fields
  • Optimize polynomial degree selection to balance model complexity and predictive power
  • Interpret coefficients and polynomial terms to understand variable relationships and data trends
  • Visualize polynomial regression fits to communicate insights effectively to stakeholders
  • Troubleshoot common issues in polynomial regression modeling, including multicollinearity and data scaling

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Lessons | 25


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Siddharth Singh 

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2024-05-17

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