Data Science & Analytics
Evaluating and Finalizing Your Feature-Driven Model
This course shows how feature engineering should change across models like Linear Regression, Random Forest, and LightGBM. You’ll build and test model-specific features, compare results with RMSE, and refine your pipeline based on evidence.
Numpy
Pandas
Python
sklearn
3 lessons
14 practices
2 hours
Programming and Algorithms
Course details
Linear Regression Feature Optimization
Creating Binary Features for Linear Models
Creating Ratio Features for Linear Models
Evaluating the Impact of Feature Rounding on Linear Regression Performance
Beyond Rounding: Strategic Binning to Boost Linear Model Performance
Modularizing Your Final Linear Regression Features
Join the 1M+ learners on CodeSignal
Be a part of our community of 1M+ users who develop and demonstrate their skills on CodeSignal
