Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

There's been a seismic shift in science, with scientists developing new AI tools and applying AI to just about any question that can be asked. Researchers are now putting actual seismic waves to work, ...

Here's a statistical challenge worthy of a grandmaster: How do you create an accurate ranking system when the best players ...

The Department for Work and Pensions (DWP) has published a “data strategy” document that sets out what it believes it will ...

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...

• Invest in data readiness. Informatica’s CDO survey notes that data quality and readiness (43%), technical maturity (43%) and skill shortages (35%) are the top obstacles to AI success. Winning ...

This book, “Statistical Modeling and Computation,” provides a unique introduction to modern statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

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 ...

Outside of tightly controlled environments, most robotic systems still struggle with reliability, generalization and cost. The gap between what we can demonstrate and what we can operate at scale ...