How Machine Learning Algorithms Work (they learn a mapping of input to output)

Last Updated on August 12, 2019

How do machine learning algorithms work?

There is a common principle that underlies all supervised machine learning algorithms for predictive modeling.

In this post you will discover how machine learning algorithms actually work by understanding the common principle that underlies all algorithms.

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Learning a Function

Machine learning algorithms are described as learning a target function (f) that best maps input variables (X) to an output variable (Y).

Y = f(X)

This is a general learning task where we would like to make predictions in the future (Y) given new examples of input variables (X).

We don’t know what the function (f) looks like or it’s form. If we did, we would use it directly and we would not need to learn it from data using machine
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