Survival analysis, the branch of statistics devoted to modeling the time until an event occurs, has long been a stronghold of ...

Computational psychiatry has grown rapidly, but modeling approaches remain fragmented and inconsistently implemented across labs. Differences in code, assumptions, and documentation can make results ...

A lot of people, at least in the pre-"vibe coding era," lament that they can't program because they're "not math people." I wasn't either. Here's how I got started building machine learning models in ...

One decision many enterprises have to make when implementing AI use cases revolves around connecting their data sources to the models they’re using. Different frameworks like LangChain exist to ...

Most projects benefit from having a data model. This article gives an overview of the most common types. At its heart, data modeling is about understanding how data flows through a system. Just as a ...

The Covid-19 pandemic reminded us that everyday life is full of interdependencies. The data models and logic for tracking the progress of the pandemic, understanding its spread in the population, ...

As more organizations embrace big data and analytics to gain insight from extremely large datasets, the tools and systems used to manage data have grown, changed, and mul­tiplied. Instead of just ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...