An intuitive guide to Gaussian processes – Towards Data Science

Machine learning is using data we have (known as training data) to learn a function that we can use to make predictions about data we don't have yet. The simplest example of this is linear regression, where we learn the slope and intercept of a line so we can predict the vertical position of points from their horizontal position. This is shown below, the training data are the blue points and the learnt function is the red line. Machine learning is an extension of linear regression in a few ways. Secondly, modern ML uses much more powerful methods for extracting patterns of which deep learning is only one of many.