Predictive analytics is the use of statistics and modeling techniques to determine future performance based on current and historical data.

Predictive modeling uses known results to create, process, and validate a model that can be used to forecast future outcomes.

The results aren't true 3D models, but they achieve a similar effect: The AI tool generates 2D video frames that maintain ...

This white paper by industry expert Alec Sharp illustrates these points and provides specific guidelines and techniques for a business-oriented approach to data modeling. Examples demonstrate how ...

The rapid expansion of the Web has necessitated the development of advanced data management techniques capable of handling imprecision and uncertainty. Fuzzy data modelling offers a rigorous ...

The surge in AI-driven studies aligns with the sector’s reliance on predictive analytics and machine learning models to identify learning patterns, assess performance risks, and personalize support ...

Claybrook is an experimental AI model developed by Google and the model’s focus is on web development with an emphasis frontend tasks such as UI/UX coding. Claybrook leverages advanced techniques, ...

The analysis of data from dose-response studies has long been divided according to two major strategies: multiple comparison procedures and model-based approaches. Model-based approaches assume a ...

In this post, we will outline some of the modeling assumptions and techniques of the Solovis Risk tool that enable us to model our clients’ multi-asset class portfolios.