Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

For our getting-dressed example, a machine learning algorithm would be the equivalent of your remembering past decisions about what to wear, knowing how comfortable you feel wearing each item, and ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine ...

From there, the algorithms complete some sort of machine learning task, like identifying motorcycles from trucks, as you might do in one of those RECAPTCHA tests that checks to see whether or not ...

Our example machine learning exercise had an extremely simple algorithm to build as we only needed to derive an equation in this form: Salary = Years of Service * X + $45,000 (aka y = mx + b).

Machine learning and its subsets are useful for a wide range of problems, tasks, and applications. There’s computer vision, which allows computers to “see” and make sense of images and videos.

Facebook uses various machine learning algorithms to sort content, including the “holistic” assessment tool known as WPIE. Image: Facebook ...