Learn how to implement linear regression in Python using the Boston Housing dataset. The post covers key concepts like cost computation, gradient descent, and feature scaling, and it demonstrates how to improve model performance through regularization techniques such as Ridge and LASSO regression. Step-by-step code examples are provided to help you understand the underlying processes and achieve optimal results.
Table of contents
Predict Housing Price using Linear Regression in PythonWhat is Linear RegressionData DescriptionCost ComputationGradient DescentPredictionResult EvaluationFeature ScalingRegularization — Ridge RegressionRegularization — LASSO RegressionInterpreting the ResultsSummaryReferencesSort: