Introduction to Data Modeling with Scikit-Learn

This tutorial focuses on applying Scikit-Learn for fundamental data modeling tasks. It begins with an overview of objectives and learning content, including linear regression and decision tree methodologies.

The content includes detailed code examples demonstrating data loading, preprocessing, model implementation, and evaluation. Key steps involve importing libraries, handling the Boston housing dataset, splitting data into training/test sets, and training both linear regression and decision tree models.

Evaluation metrics such as mean squared error (MSE) and R² score are emphasized, along with visualization of prediction results. The tutorial concludes with practical implementation guidance for real-world applications.