Linear Regression with Scikit-learn:

Completed a program by applying linear regression to predict house prices from the Boston housing dataset using scikit-learn and compared train and test scores and plot residuals.

This Python script utilizes the Boston housing dataset to perform linear regression. After splitting the data into training and testing sets, it trains a linear regression model on the training data and evaluates its performance on both sets. It calculates the model's scores for training and testing data. Additionally, it visualizes the residuals, highlighting discrepancies between predicted and actual values. This analysis aids in assessing the model's fit and identifying potential areas for improvement, crucial for understanding predictive accuracy and model effectiveness in real-world applications.