AEquity aims to improve training for healthcare machine-learning algorithms by assessing the accuracy and fairness of the data they're fed.

Github has assembled a wealth of resources for machine learning activities, including a list of the top public domain datasets.

The go-to for data scientists seeking huge datasets. Thousands of datasets span themes from AI to finance to health, and they ...

A screenshot of mislabeled images from ImageNet, a dataset used to test machine learning systems. In one instance, it applied a "nipple" label to a photo of a baby. The datasets, which have each ...

Unifying machine learning datasets within a single data format makes it easier for organizations to transition to data-centric AI and step into a new era of innovation.

Datasets in AI and machine learning contain many flaws. Some might be fixable, according to experts -- given enough time and resources.

In recent years, machine learning has revolutionized the study of glacier erosion rates, providing valuable insights into ...

If the datasets used to train machine-learning models contain biased data, it is likely the system could exhibit that same bias when it makes decisions in practice.