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 ...

Machine learning (ML) algorithms that incorporate routinely collected patient-reported outcomes (PROs) alongside electronic health record (EHR) variables may improve prediction of short-term mortality ...

At the conceptual intersection of machine learning and government data collection lie Automated Suspicion Algorithms, or ASAs, which are created by applying machine learning methods to collections of ...

Machine learning algorithms are the engines of machine learning, meaning it is the algorithms that turn a data set into a model.

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.

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.

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

Data scientists are struggling to make their machine-learning models transparent to comply with upcoming European legislation.