The objective is to determine whether a given data point fits an existing pattern or if it is an outlier or anomaly, and as a result find what fits with existing data and what doesn’t.

walks you through a discussion between IBM’s Stephen Archut and Dr. Girish Punj, professor of marketing, looking at data, patterns and decisions made within the marketing landscape.

Predictive analytics is the process of using data to find patterns, trends and relationships. The purpose of predictive analytics is to solve a problem by using data to deepen our understanding and ...

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 ...

The algorithms used to crunch this ocean of data in search of predictable patterns are enhanced through machine learning, through which they are automatically fine-tuned based on results.

Did it seem plausible? That is because humans love to find patterns, especially in large data sets. We don't even know we're doing it (notice how Mary can show up on a potato chip?) Yet ...

A new study unearthed patterns in datasets collected on ... applied a fresh perspective to vast amounts of data on rice plants to find better ways to predict plant performance and new insights ...

A KAUST team is taking a creative, combined deep learning approach that uses data from multiple sources to teach algorithms how to find patterns between genes and diseases. Machine learning uses ...