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 ...

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.

Machine-learning algorithms find and apply patterns in data. And they pretty much run the world. Machine-learning algorithms are responsible for the vast majority of the artificial intelligence ...

Our latest Methods 101 video explains the basics of machine learning and how it allows our researchers to analyze data on a large scale.

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 ...

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 ...

This study employed machine learning – support vector machines (SVM) – to determine whether such structures can be automatically extracted from LiDAR data and classified using computerised techniques.

He’s credited with coming up with the first support vector machine (SVM) algorithm. SVMs are widely used today for machine learning purposes.