Then we discuss some specific methods from the ML literature that we view as important for empirical researchers in economics. These include supervised learning methods for regression and ...

This issue has now been addressed. Li Hang's newly launched book 'Machine Learning Methods (2nd Edition)' dedicates a chapter ...

The development of every field relies on a few foundational classic books, and artificial intelligence is no exception.

Our findings suggest that integrating machine learning into traditional statistical methods can provide more accurate and generalizable models for disease risk prediction.

Gynecological cancers, including breast, ovarian, and cervical malignancies, account for a significant global health burden among women. The review outlines how a spectrum of machine learning (ML) ...

Researchers used satellite data to map air pollution across Ghana from 2003-2019, finding higher levels in the southwest likely due to vegetation & mining.

Regression is a vital tool for predicting outcomes in investing and other pursuits. Find out what it means when applied to machine learning.

The time-tested technique for predicting numbers, and the role of domain knowledge in machine learning.