This ebook, based on the latest ZDNet / TechRepublic special feature, explores how you set up an analytics infrastructure that sees around corners and gives you options to avoid a head-on crash. Read ...

Models are important for understanding the current and future states of the world and we use many, for instance the capital asset pricing model, to help us understand markets and investing. But most ...

As predictive models proliferate, providers and decision makers require accessible information to guide their use. Preventing and combating bias must also be priorities in model development and in ...

Large language models can act as predictive models. Here's an example for misinformation detection—and an introduction to savings curves. Not all business problems are best addressed with generative ...

Predictive models are used across the student life cycle in higher education, to gauge yield in admissions as well as retention and graduation initiatives, as campus leaders look to understand what ...

Overview:  Enterprises use four main types of analytics: descriptive, diagnostic, predictive, and prescriptive.Each type answers a different business quest ...

Inaccurate or overlooked alerts on manufacturing data can be reduced with proper data handling when developing and deploying predictive models. Data analytics, and specifically predictive analytics, ...

Patients are less comfortable with predictive models used for health care administration compared with those used in clinical practice, signaling misalignment between patient comfort, policy, and ...

Before 2017, Zuckerberg San Francisco General Hospital – an urban, academic safety-net hospital within the San Francisco Health Network – struggled with some of the highest 30-day readmission rates in ...