Azure Learning

Real-world scenario

By applying the preprocessing techniques outlined in this guide, you can:

• Impute missing incomes and remove duplicate records to create a clean dataset.


• Standardize numerical features such as income and credit scores to bring them to a uniform scale.


• Encode job titles into numerical values, allowing algorithms to interpret them eff

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Use the Evaluate Model to see how well the trained model performed on the test dataset.

Right-click the Evaluate Model component and select Preview data > Evaluation results to view its output.

The following statistics are shown for your model:

• Mean Absolute Error (MAE) : The average of absolute errors. An error is the difference between the p

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