There are a few different types of predictive modeling. Find out what makes each unique and how you can use them in your data projects.

Data modeling is the framework that lets data analysis use data for decision-making. A combined approach is needed to maximize data insights.

The core of the Python data model architecture is special methods (also known as "magic methods"). These methods, which start ...

A data model is a visual representation of data elements and the relations between them.

Physical data model. The final layer is physical and represents a composition of host system artifacts—physical data objects—derived from a logical data model coupled with its desired storage ...

A novel approach from the Allen Institute for AI enables data to be removed from an artificial intelligence model even after it has already been used for training.

The advent of large language models in text, search and image processing has undeniably revolutionized the landscape of unstructured data.

What Are AI Models? AI models are mathematical representations of real-world phenomena, designed to learn patterns from massive data in order to make decisions without further human intervention.

Better data annotation—more accurate, detailed or contextually rich—can drastically improve an AI system’s performance, adaptability and fairness.