Machine-learning algorithms use statistics to find patterns in massive* amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you.

History of machine learning. ML’s rise began with a humble checkers game and has since rewritten the rulebook of what computers can do. Let’s dive into this data-driven tale.

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

The first step when working with any machine learning data file is to do a preliminary investigation. The source data is named people_no_missing.txt ("no missing columns") and has only 13 lines to ...

Machine Learning continues to transform the ways we live our lives and run our businesses. However, the meaning and implications of what machine learning is in 2017 are not fully understood by ...

Machine learning seems to be all the rage these days. But what is it exactly? Broadly speaking, machine learning (ML) is a subset of artificial intelligence that allows systems to learn from data ...

Our latest video explainer – part of our Methods 101 series – explains the basics of machine learning and how it allows researchers at the Center to analyze data on a large scale. To learn more about ...

Novelty and outlier detection is (yet another) large, exciting and growing use for machine learning. As usual with machine learning, the problem is not one of coding, but rather of massaging the data ...

Since machine learning governs computers rather than rules-based engines, with each processing of an image by the algorithms that underpin computer vision platforms, the computer refines its ...

Machine learning is the process by which computer programs grow from experience. This isn’t science fiction, where robots advance until they take over the world. When we talk about machine ...