Learning algorithms already make a lot of important decisions every day, from who gets credit to who gets interviewed for a job to who gets flagged as a potential terrorist. And they make mistakes.

Today, computer programs use machine-learning algorithms to study piles of data and learn about the world and its people. Algorithms can tell a banker whether someone will pay back a loan.

Core machine learning engineer: Computer science fundamentals and programming, applying machine learning algorithms and libraries, data modeling, and evaluation ...

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.

Researchers have devised a new framework for designing machine learning algorithms that helps prevent intelligent machines from being biased.

These quantum machine learning algorithms can handle high-dimensional data and complex patterns that traditional machine learning algorithms struggle to address.

It doesn’t take much to make machine-learning algorithms go awry The rise of large-language models could make the problem worse ...

The human-like learning wasn't limited to recognizing characters, either. The computer could also figure out how to write them using a series of pen strokes (created on a screen).

Over the past decades, computer scientists have developed increasingly sophisticated sensors and machine learning algorithms ...