Applications for machine learning. The field of machine learning is very active right now, with many common applications in business, academia, and industry. Here are a few representative examples: ...

Types of Adaptive Learning The EGA researchers concluded that technology vendors offering truly "rigorous adaptive learning solutions" leverage numerous areas of academic research, including ...

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.

Continual learning is integral to the human experience. People who can learn faster and better than others tend to do well in life. The same is true for successful organizations. Machine learning ...

Game-playing machine learning is strongly successful for checkers, chess, shogi, and Go, having beaten human world champions. Automatic language translation has been largely successful, although ...

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 ...

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 and AI. Getty. One of the downsides to the recent revival and popularity of Artificial Intelligence (AI) is that we see a lot of vendors, professional services firms, and end ...

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 ...