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advanced-did-isr

adversarial_gmm

Prototype code for paper: Adversarial Generalized Method of Moments, Greg Lewis and Vasilis Syrgkanis

business-data-science

Code and examples from Business Data Science

causal-inference-1

Causal Inference 1 Mixtape Session

causal-inference-2

Causal Inference II Mixtape Session

causal-inference-in-python-code

Code for the Book Causal Inference in Python

causalml

Uplift modeling and causal inference with machine learning algorithms

cs_rr

datascienceprojects

The code repository for projects and tutorials in R and Python that covers a variety of topics in data visualization, statistics sports analytics and general application of probability theory.

datastream-worldscope-fundamental-dataset

This guide aims to be a full instruction on how to download and merge Refinitiv (formerly Thomson Reuters) Datastream Worldscope data into one comprehensive dataset of yearly stock quoted financial statements.

ddml

ddml: Double/Debiased Machine Learning in R

developing-kaggle-notebooks

did-confounding-supplementary

Supplementary materials for "Confounding and Regression Adjustment in Difference-in-Differences Studies"

differences-in-python

difference-in-differences in Python

double-ml-paper

econ622-data-science-in-economics

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 in

fall-2020

github-for-social-scientists

This is a Hello World for economists using Stata and Dropbox!

god-level-data-science-ml-full-stack

A collection of scientific methods, processes, algorithms, and systems to build stories & models. Whether you are a fresher in the field or an experienced professional who wants to transition into Data Science & AI

grad-io

Graduate Empirical Industrial Organization

honestdid

Robust inference in difference-in-differences and event study designs

jsrt_unet

This project implements an instance segmentation model using the UNET architecture to precisely identify and segment lungs and heart structures in medical images from the JSRT dataset. The goal is to provide accurate delineation of these organs, aiding in medical image analysis and diagnosis.

lost-stats.github.io

Source code for the Library of Statistical Techniques

machine-learning-collection

A resource for learning about Machine learning & Deep Learning

machine-learning-specialization-coursera

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

mitx_6.86x

Notes of MITx 6.86x - Machine Learning with Python: from Linear Models to Deep Learning

phd-industrial-organization

In this repository I collect the lecture notes and code for an advanced course in Empirical Industrial Organization. All code is written in Julia.

pretrends

R package for power calculations and visualization for pre-trends tests

reproducingdmldid

original paper: Chang, Neng-Chieh. "Double/debiased machine learning for difference-in-differences models." The Econometrics Journal 23.2 (2020): 177-191