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Dennis Lyubyvy's Projects

causalml icon causalml

Uplift modeling and causal inference with machine learning algorithms

dowhy icon dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

econml icon 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.

erlangr icon erlangr

Set of functions to calculate call center agents and trunks requirements using ErlangB and ErlangC functions in R

freqtrade icon freqtrade

Simple High Frequency Trading Bot for crypto currencies

patient2vec icon patient2vec

Patient2Vec: A Personalized Interpretable Deep Representation of the Longitudinal Electronic Health Record

scikit-uplift icon scikit-uplift

:exclamation: uplift modeling in scikit-learn style in python :snake:

team-shiny icon team-shiny

Columbia University STAT 4701 Spring 2015 "Team Shiny" repo

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