Python Machine Learning - Code Examples

• Introducing a simple linear regression model
• Exploring the Housing Dataset
  • Visualizing the important characteristics of a dataset
• Implementing an ordinary least squares linear regression model
  • Solving regression for regression parameters with gradient descent
  • Estimating the coefficient of a regression model via scikit-learn
• Fitting a robust regression model using RANSAC
• Evaluating the performance of linear regression models
• Using regularized methods for regression
• Turning a linear regression model into a curve – polynomial regression
  • Modeling nonlinear relationships in the Housing Dataset
  • Dealing with nonlinear relationships using random forests
    • Decision tree regression
    • Random forest regression
• Summary