Machine learning ain't all input/output There's a paper in the journal PLoS Computational Biology that is incredibly significant to folks thinking through the intersection of human-computer ...

Machine learning deals with software systems capable of changing in response to training data. ... Many neural networks distinguish between three layers of nodes: input, hidden, and output.

In this way, machine learning enables a computer to learn how to perform a task on its own and to continue to optimize its approach over time, without direct human input.

Machine learning can be supervised, unsupervised, or semi-supervised. In supervised learning, models are trained on labeled data, meaning the input data is paired with the correct output.