Researchers use statistical physics and "toy models" to explain how neural networks avoid overfitting and stabilize learning in high-dimensional spaces.

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

Machine learning sounds math-heavy, but modern tools make it far more accessible. Here’s how I built models without deep math ...

History suggests that extreme run-ups in the cyclically adjusted price-earnings ratio are a signal that the stock market may be overvalued. A simple regression model using a small set of macroeconomic ...