Summary
In this module, you learned how to use regression to create a machine learning model that predicts numeric values. You did some exploratory data analysis by using the Tidyverse. Then you used the tidymodels framework in R to:
- Train and evaluate a regression model by using different algorithms.
- Do some data preprocessing.
- Tune some hyperparameters.
- Make better predictions.
Tidymodels and scikit-learn (Python) are popular frameworks for writing code to train regression models. You can also create machine learning solutions for regression by using the graphical tools in Azure Machine Learning. To learn more about no-code development of regression models by using Machine Learning, see Create a regression model with Azure Machine Learning designer.