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Gradient boosting: It's really a form of machine Mastering algorithm that could make predictions about the best possible following model determined by the past versions, thus reducing the prediction errors. Additionally, it sets a concentrate on outcome for the following model to chop down the errors. 

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Illustration: Assuming that a can be a numeric variable, the assignment a := 2*a signifies that the articles with the variable a is doubled once the execution with the assertion.

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Loops: Loops would be the conditional statement that is executed as long as the conditional statement returns correct.

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