Simple Linear Regression

In this notebook you will use data on house sales in King County from Kaggle to predict house prices using simple (one input) linear regression. You will:

  • Use graphlab SArray and SFrame functions to compute important summary statistics
  • Write a function to compute the Simple Linear Regression weights using the closed form solution
  • Write a function to make predictions of the target given the input feature
  • Turn the regression around to predict the input given the target
  • Compare two different models for predicting house prices
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Multiple Regression

In this notebook you will use data on house sales in King County from Kaggle to predict prices using multiple regression. We will:

  • Use SFrames to do some feature engineering
  • Use built-in turicreate functions to compute the regression weights (coefficients/parameters)
  • Given the regression weights, predictors and outcome write a function to compute the Residual Sum of Squares
  • Look at coefficients and interpret their meanings
  • Evaluate multiple models via RSS
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