Noticias sobre Python y Datos de la semana, episodio 73 🐍⚙️

En resumen: Versiones nuevas de JupySQL, Modin, Prefect y más, machine learning "doble", detección de comunidades en grafos, ojo a la chi2 de scikit-learn, y noticias del viejo Spyder

https://astrojuanlu.substack.com/p/episodio-73

Apoya el noticiero suscribiéndote por correo 📬

#python #pydata #jupysql #ploomber #modin #prefect #doubleml #networkx #sklearn #spyder

1. Stats/’metrics recap:
- Conditional Expectation Functions and how to model them
- Convergence rates
Both play a crucial role for #DoubleML and students tend to have no good intuition what the latter means
https://nbviewer.org/github/MCKnaus

Hi! #introduction by paper

Do you 👍 #causalML to estimate CATEs? Me too 🤓

With Phillip Heiler, I take a step back and ask what CATEs actually mean if a 0/1 "treatment" is itself heterogeneous (binarized multi trmt or multi trmt versions).

2 new features of a 1yo paper:

You 👍 intution on #causalinference?
😀-based intro to the issue https://t.co/WkDIf9HxyN

You 👍 #econometrics theory?
Updated #DoubleML theory allows no. of trmts -> ∞ -> extreme pscores (limited overlap) https://arxiv.org/abs/2110.01427