Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests.

Machine learning is a field of artificial intelligence (AI) that keeps a computer’s built-in algorithms current regardless of changes in the worldwide economy.

20 Gianfrancesco MA, Tamang S, Yazdany J, Schmajuk G. Potential biases in machine learning algorithms using electronic health record data. JAMA Intern Med. 2018;178 (11):1544–7.

Want to understand how machine learning impacts search? Learn how Google uses machine learning models and algorithms in search.

From Apple to Google to Toyota, companies across the world are pouring resources into developing AI systems with machine learning. This comprehensive guide explains what machine learning really means.

Machine learning is hard. Algorithms in a particular use case often either don't work or don't work well enough, leading to some serious debugging. And finding the perfect algorithm–the set of ...

Meta-Learning This is a less popular type of machine learning algorithm, but in many ways, it is both the easiest to understand and the most powerful.

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.

A special category of algorithms, machine learning algorithms, try to “learn” based on a set of past decision-making examples.

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

Proximal algorithms are useful for obtaining solutions to difficult optimization problems, especially those involving nonsmooth or composite objective functions. A proximal algorithm is one whose ...