Why Do Machine Learning Algorithms Work on New Data?

Last Updated on July 5, 2019

The superpower of machine learning is generalization.

I recently got the question:

“How can a machine learning model make accurate predictions on data that it has not seen before?”

The answer is generalization, and this is the capability that we seek when we apply machine learning to challenging problems.

In this post, you will discover generalization, the superpower of machine learning

After reading this post, you will know:

• That machine learning algorithms all seek to learn a mapping from inputs to outputs.
• That simpler skillful machine learning models are easier to understand and more robust.
• That machine learning is only suitable when the problem requires generalization.

Let’s get started.

What Do Machine Learning Algorithms Do?

When we fit a machine learning algorithm, we require a training dataset.

This training dataset includes a set of input patterns and the corresponding output
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