- Introducing regression
- Simple linear regression
- Exploring the Ames Housing Dataset
- Loading the Ames Housing dataset into a data frame
- 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 Ames Housing dataset
- Dealing with nonlinear relationships using random forests
- Decision tree regression
- Random forest regression
- Summary
Please refer to the README.md file in ../ch01 for more information about running the code examples.