Bigboats

WeightIt

WeightIt: an R package for propensity score weighting

causalml

Uplift modeling and causal inference with machine learning algorithms

entbal

An Alternative Implementation of Entropy Balancing Weights For Estimating Causal Effects

free

翻墙、免费翻墙、免费科学上网、免费节点、免费梯子、免费ss/v2ray/trojan节点、蓝灯、谷歌商店、翻墙梯子

grf

Generalized Random Forests

Building-Machine-Learning-Systems-with-Python-Third-edition

Code repository for Building Machine Learning Systems with Python Third Edition, by Packt

PythonTutor

Python教学

Conditional_Density_Estimation

Package implementing various parametric and nonparametric methods for conditional density estimation

deep-learning-from-scratch

《深度学习入门-基于Python的理论与实现》，包含源代码和高清PDF(带书签)；慕课网imooc《深度学习之神经网络(CNN-RNN-GAN)算法原理-实战》；《菜菜的机器学习sklearn》

causalLearning

Methods for heterogeneous treatment effect estimation

MLInference

machine_learning_step_by_step

Machine learning algorithms step by step with explanation

dragonnet

Python-Regression-Tree-Forest

Python implementation of CART regression tree and random forests

CTL

A causal tree method for heterogeneous treatment effects in Python

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.

scikit-learn

A version of scikit-learn that includes implementations of Wager & Athey and Scott Powers causal forests.

causalTree

Working repository for Causal Tree and extensions

statsmodels

Statsmodels: statistical modeling and econometrics in Python

CTL

A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python

SP19-DL-collaborative-notes

Collaborative lecture notes for Spring '19 NYU DL class

lihang-code

《统计学习方法》的代码实现

Machine-Learning-Foundations-Techniques

interpretable-ml-book

Book about interpretable machine learning

numpy-ml

Machine learning, in numpy

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

Virgilio

Your new Mentor for Data Science E-Learning.

ailearning

AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

interesting-python

有趣的Python爬虫和Python数据分析小项目(Some interesting Python crawlers and data analysis projects)

Coursera-ML-AndrewNg-Notes

吴恩达老师的机器学习课程个人笔记