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.

With how common machine learning has become today, you may wonder how it works and what its limitations are. So here’s a simple primer on the technology.

Machine learning allows an AI to change the topography of its decision ... Association is the fundamental unit of learning.

Machine Learning 101. So, what is machine learning in the first place? ... Association is the fundamental unit of learning. In a way, this mimics simple conditioning, like Pavlov and his dogs.

Machine learning is the field behind a great many of the artificial intelligence programs that we encounter in daily life right now. It’s a method that AI tools use to acquire new information.

Unsupervised learning is where the machine is trained using a dataset that doesn’t have any labeling. The learning algorithm is never told what the data represents. Here is a letter, but no ...

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.

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.