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.

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

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.

Researchers used fMRI technology to monitor the brain activity of volunteers as they interacted with "experts" -- some human, others computer algorithms -- to predict the behavior of a ...

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.

Machine Learning is a sub-set of artificial intelligence where computer algorithms are used to autonomously learn from data and information.

Deep learning is a form of machine learning that models patterns in data as complex, multi-layered networks. Because deep learning is the most general way to model a problem, it has the potential ...

Similar analogies exist in the area of autonomous vehicles. Overall, machine learning seems to define the notion of probabilistic algorithms in computer science in a similar manner as quantum physics.

Quantum machine learning software could enable quantum computers to learn complex patterns in data more efficiently than classical computers are able to.