It’s no surprise to anyone that most business’ analytics and decision-making processes have been completely transformed by the data afforded to us by the rapidly changing technological age. That said, ...

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, ...

The following article is an excerpt (Chapter 3) from the book Hands-On Big Data Modeling by James Lee, Tao Wei, and Suresh Kumar Mukhiya published by our friends over at Packt. The article addresses ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

Many engineering teams still rely on architecture optimized for transactional apps, not for AI systems that mix structured and unstructured data and live event streams. This legacy architecture has ...

Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...

Artificial intelligence (AI) is rapidly transforming medicine, promising to revolutionize diagnostics, treatment planning and operational efficiency. But there’s a critical—and often overlooked—flaw ...