Machine learning is a branch of artificial intelligence that includes ... Decision Tree, Logistic Regression, K-Nearest Neighbors, and Support Vector Machine (SVM). You can also use ensemble ...

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.

To a large extent, supervised ML is for domains where automated machine learning does not perform well enough. Scientists add supervision to bring the performance up to an acceptable level.

SVM and kNN exemplify several important trade-offs in machine learning (ML). SVM is often less computationally demanding than kNN and is easier to interpret, but it can identify only a limited set ...

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 ...

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 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 ...

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 ...