Optimizing Feature Engineering for Small Datasets

[Shaikhasna]

Hello everyone,

While experimenting with the regression notebooks, I noticed that feature selection and transformation significantly impact performance on smaller datasets.

What strategies or transformations do you recommend to maximize model performance while avoiding overfitting, especially in beginner-friendly pipelines? Are there practical ways to visualize feature importance for learners?