Lesson 2: Feature Engineering and Regression Modeling
Lesson Overview
Develop practical capability in feature engineering and regression modeling as part of the MATLAB for Data Analysis and Predictive Modeling learning path.
Topics Covered
Predictor selection and transformation
Linear and polynomial regression
Regularization concepts
Regression Learner workflow
Residual diagnostics
Continuous-response performance metrics
Practical Activity
Build a guided MATLAB exercise covering predictor selection and transformation.
Apply linear and polynomial regression to a practical engineering or data scenario.
Validate results and troubleshoot an issue involving continuous-response performance metrics.
Key Takeaways
Explain and apply predictor selection and transformation.
Use regularization concepts in a structured workflow.
Validate outputs with plots, metrics, tests, or simulation evidence.
