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Sebastian Raschka, 2015

Python Machine Learning - Code Examples

Chapter 10 - Predicting Continuous Target Variables with Regression Analysis

  • 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