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

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

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.

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.

But AI is not only about large data sets, and research in “small data” approaches has grown extensively over the past decade—with so-called transfer learning as an especially promising example.

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 ...