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

Supervised learning algorithms learn from labeled data, where the desired output is known. These algorithms aim to build a model that can predict the output for new, unseen input data. Let’s take a ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...

A backpropagation algorithm, or backward propagation of errors, is an algorithm that's used to help train neural network models. The algorithm adjusts the network's weights to minimize any gaps -- ...

To continue reading this content, please enable JavaScript in your browser settings and refresh this page. Whether it is chatbots for customer interaction, neural ...

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms—addressing a ...

Algorithms now make lots of decisions, but they have their own biases, writes Wharton’s Kartik Hosanagar in his new book. When we buy something on Amazon or watch something on Netflix, we think it’s ...

I was halfway through a master’s in Computer Science when my vision changed. I was working as a data scientist during my summer off from school, and I had friends who said things like “I’m at a local ...

An algorithm commonly used by hospitals and other health systems to predict which patients are most likely to need follow-up care classified white patients overall as being more ill than black ...