Machine Learning

Train a machine learning model with scaled training data, predict with test data, and visualize predictions.

Let's create a machine learning model using a linear regression module from scikit-learn to suggest the house price based on the selected features.

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Let’s say we have cleaned our data, treated the missing values and categorical variables, removed outliers, and created required new features (if needed). Now, our data is ready to feed into the machine learning model. The very first thing to do now is to separate our data into the following:

  • X: Will contain the selected features, also called independent variables.

  • y: Will be the target values; in this case, the house price is also called the dependent variable.

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