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abma

SantaFeInstitute/ABMA: the code repository and website for Agent-Based Modeling for Archaeology.

agentpy

AgentPy is an open-source framework for the development and analysis of agent-based models in Python.

alc_labelling

Análisis de las caracteristicas de una muestra de etiquetas de bebidas alcohólicas

analisis_operaciones_aereas_mexico

Análisis de las operaciones aéreas en México, con especial atención al Sistema Aeroportuario Metropolitano

applied-methods-phd

Repo for Yale Applied Empirical Methods PHD Course

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

awesome-shiny-extensions

🐝 Awesome R packages that offer extended UI or server components for the R web framework Shiny

bayes-prevalence

biogpt

causaldata

Packages of Example Data for The Effect

cdc-open-viz

CDC OpenViz is a library of React packages for data visualization.

censo

Cálculos y visualizaciones con datos censales

computer-science

:mortar_board: Path to a free self-taught education in Computer Science!

cornell-cs5785-2020-applied-ml

Teaching materials for the applied machine learning course at Cornell Tech (online edition)

courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

critical-data-book

Code repository for the critical data book

cs-video-courses

List of Computer Science courses with video lectures.

curso-series-temporales

datasciencecoursera

Data Science Project for Coursera "The Data Scientist’s Toolbox" course

datasharing

The Leek group guide to data sharing

ddp_shinyapp

Shiny App for the final assignment of Coursera's Develping Data Products course

depresionensanut18

developing_data_products

Developing Data Products Course from the Johns Hopkins Data Science Lab

did2s

Two-stage Difference-in-Differences package following Gardner (2021)

diff-in-diff-notes

Keeping track of what is going on with the latest DiD innovations.

dismod_mr

An Integrative Metaregression Framework for Descriptive Epidemiology

eda_week1_r

Exploratory Data Analysis R Course: Course Project 1

fast_feature_selection

Genetic algorithms and CMA-ES (covariance matrix adaptation evolution strategy) for efficient feature selection

geostatspy_intro_course

Introduction to spatial data analytics and machine learning with GeostatsPy Python package

getting-and-cleaning-data