liukanglucky's Stars
datawhalechina/easy-rl
强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/
crflynn/skgrf
scikit-learn compatible Python bindings for grf (generalized random forests) C++ random forest library
py-why/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.
timmens/causal-forest
Implements the Causal Forest algorithm formulated in Athey and Wager (2018).
kjung/scikit-learn
A version of scikit-learn that includes implementations of Wager & Athey and Scott Powers causal forests.
grf-labs/grf
Generalized Random Forests
shenweichen/DeepCTR
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .