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computational-social-science-training-program

This course is a rigorous, year-long introduction to computational social science. We cover topics spanning reproducibility and collaboration, machine learning, natural language processing, and causal inference. This course has a strong applied focus with emphasis placed on doing computational social science.

dime-standards

Repository with resources for DIME's research standards and coding standards

gaza_projections

Scenario-based health impact projections of the war in Gaza (2023-2024)

generative-ai-for-beginners

18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

high-frequency-checks

A Stata template for running high frequency checks of incoming research data at Innovations for Poverty Action

iqual

iQual is a package that leverages natural language processing to scale up interpretative qualitative analysis. It also provides methods to assess the bias, interpretability and efficiency of the machine-enhanced codes. iQual has been applied to analyse interviews on parents' aspirations for their children in Cox's Bazaar, Bangladesh.

nicole.ywu.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

panelcombine

Workspace for STATA code to combine LaTeX-formatted regression output tables from estout/esttab

ramresourcesscripts

A public space for contributing to WFP's corporate Needs Assessment and Monitoring analysis of micro-data.

templates

Templates of all kind

togo-targeting-replication