Bryan S Weber's starred repositories
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.
permafrost-engine
An OpenGL RTS game engine written in C
doubleml-for-py
DoubleML - Double Machine Learning in Python
catanatron
Settlers of Catan Bot Simulator and Strong AI Player
applied-machine-learning-intensive
Applied Machine Learning Intensive
doubleml-for-r
DoubleML - Double Machine Learning in R
vgchartzScrape
Scrapy project for data capture of vgchartz
eventStudy
R package and guide for performing event studies with heterogeneous dynamic effects.
intro_access_book
Introduction to urban accessibility: a practical guide in R (https://ipeagit.github.io/intro_access_book/)
biblatex-publist
BibLaTeX bibliography support for publication lists
NFT-Dataset
Includes data about over 250 NFT Collections
CUNYAIModule
CUNYBot, an AI that plays complete games of Starcraft.
DIDmultiplegt
:exclamation: This is a read-only mirror of the CRAN R package repository. DIDmultiplegt — Estimators DID with Multiple Groups and Periods
ColonistExtensionBackend
C# Backend for the Colonist.io Chrome Extension