course on data science for economists

Streamline a data analysis process

The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).

CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior

This repository is created to support the paper 'CAMS: An Annotated Corpus for Causal Analysis of Mental health on Social media' which is submitted to Language Resources and Evaluation Conference 2022 we introduce a new dataset for Causal Analysis of Mental health illness in Social media posts (CAMS). We first introduce the annotation schema for…

Full-featured Decision Trees and Random Forests learner.

Friendly introduction to causal inference

Code for investigating the factors affecting GRDP in a provincial level, and the short‑term, long‑term, and overall effects of the affecting variables.

The repository shows an approach to perform casual inference on Breast Cancer Data. Causal inference is carried out to determine the independent, actual effect of breast cancer that is component of a larger system

My journey through data science

CausalVerse: An R toolkit expediting causal research & analysis. Streamlines complex methodologies, empowering users to unveil causal relationships with precision. Your go-to for insightful causality exploration.

Learning Dynamic Treatment Regime (DTR) via meta-learners

This is the public repository of the code implementation for KCRL.

Reversed-engineered Transformer models as a benchmark for interpretability methods

This script, titled "Multiple Regression and Causal Analysis," conducts a series of univariate, bivariate, and multivariate analyses to explore the relationship between government expenditure, gross domestic product (GDP), drug seizures, and the United Nations Drug Control Treaty.

I use Microsoft Excel to forecast house prices for Damian Realty, identify factors affecting house prices using causal analysis, and provide inferences for realty stakeholders