Causality

For simplicity we’ll examine Simpson’s paradox specializing in two cohorts, female and male adults.I’ll be the primary to confess that I struggled to grasp this idea and it took me three weekends of deep...

Monotonic constraints are key to creating machine learning models actionable, yet they're still quite unusedProceed reading on Towards Data Science »

Library 1: Bnlearn for Python.Bnlearn is a Python package that's suited to creating and analyzing Bayesian Networks, for discrete, mixed, and continuous data sets . It's designed to be ease-of-use and comprises the most-wanted...

Hacking Granger Causality Test with ML ApproachesQuite the opposite, the forecasts of Y2 are significative different with and without the addition of Y1’s features. That signifies that Y1 has a positive impact in predicting...

How data scientists approach causal inferenceIn a recent Creator Highlight Q&A, Matteo Courthoud reflected on the growing importance of constructing robust predictions, whether one works in industry or in academia:I feel in the long...