There has lately been an increasing interest towards the integration of causal inference principles into the framework of supervised machine learning. While a machine learning model that is trained to ...

Now, the industry seems to be moving even further, toward something called inference ... supervised types of learning to less supervised types of learning – from the kind of deterministic ...

This project uses Double Machine Learning (DML) to estimate the causal effect of peace agreements on reducing violence intensity. Key components include Random Forest models, cross-fitting, and panel ...

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical ...

Tutorials: Markov Logic in Natural Language Processing (NAACL-2010), Natural Language Processing for Precision Medicine (ACL-2017), Machine Reading for ... Combining Probabilistic Logic and Deep ...

New ISACA courses in machine learning will prepare practitioners to better understand the lifecycle of machine learning ...