Supervised Learning in R: Regression

The Korshub Take

This intermediate course guides learners through continuous value prediction using supervised regression models in R. It covers model fitting, training routines, and evaluation metrics, providing a comprehensive toolkit for building reliable numeric prediction pipelines.

Who It's For

R programmers, statisticians, and data analysts looking to build and evaluate regression models for numerical outcome prediction.

Key Takeaways

• Regression Modeling: Explore multiple regression model types designed to predict numeric responses from input features.
• Model Training & Fitting: Practice training supervised regression models in R with clean, structured code patterns.
• Evaluation & Prediction: Learn methods to evaluate model accuracy and generate predictions on new datasets.