dodyyfish's Stars
RamiKrispin/lang2sql
A tutorial for setting an SQL code generator with the OpenAI API
matteocourthoud/awesome-causal-inference
A curated list of causal inference libraries, resources, and applications.
Mixtape-Sessions/Causal-Inference-2
Causal Inference II Mixtape Session taught by Scott Cunningham
inciteful-xyz/inciteful-zotero-plugin
A Zotero plugin which integrates Inciteful.xyz.
MCKnaus/causalML-teaching
This repository consolidates my teaching material for "Causal Machine Learning".
Mixtape-Sessions/Causal-Inference-1
Causal Inference 1 Mixtape Session taught by Scott Cunningham
Mixtape-Sessions/Machine-Learning
Machine Learning and Causal Inference taught by Brigham Frandsen
mavpanos/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
elliottash/text_econ_2022
Materials for PhD course on text data in economics
alex-hoagland/HAD5744
Course materials for Quantitative Methods in HSR I, University of Toronto IHPME
scunning1975/mixtape
Data and Program files for Causal Inference: The Mixtape
paulgp/applied-methods-phd
Repo for Yale Applied Empirical Methods PHD Course
andrewchbaker/JFE_DID
This repo contains the code to replicate the analyses in Baker, Larcker, Wang.
gabors-data-analysis/da-coding-rstats
Coding course to complete Data Analysis in R
Dweepobotee/Econ-Resources
asjadnaqvi/stata-bimap
A Stata package for bi-variate maps
matheusfacure/python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.