Can science offer clear guidance when the ground beneath it is inherently uncertain? This question lies at the heart of many ...

Two new advanced predictive algorithms use information about a person’s health conditions and simple blood tests to ...

Statistical models and applications of probability ... Spring (even years). Numerical algorithms useful in biostatistics including likelihood maximization using the Newton-Raphson method, EM algorithm ...

Programming knowledge is strongly encouraged. Introduction to statistical concepts, models, and algorithms of machine learning. Reviews supervised learning for regression, and introduces ...

The real estate lending landscape is changing fast with the advent of machine learning (ML) and artificial intelligence (AI). For decades, risk assessment in th ...

Two new advanced predictive algorithms use information about a person's health conditions and simple blood tests to accurately predict a patient's chances of having a currently undiagnosed cancer, ...

Statistical modeling lies at the heart of data science. Well-crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In ...

Models and algorithms we use We use a variety of models but mainly classification and forecasting. For these we use different models depending on what works best for the project mainly decision trees ...

Presents a study of theoretical concepts, statistical models, and practical applications in educational and psychological measurement. General topics include the history of measurement, Thurstone and ...

Two new advanced predictive algorithms use information about a person's health conditions and simple blood tests to accurately predict a patient's chances of having a currently undiagnosed cancer, ...