Pinned Repositories
algo-dictionary
bilibili-API-collect
哔哩哔哩-API收集整理【不断更新中....】
Coursera-ML-AndrewNg-Notes
吴恩达老师的机器学习课程个人笔记
cvx_short_course
Materials for a short course on convex optimization.
datastructs_and_algorithm
Data struct and algorithm introduction and implementation in C/C++/Java.
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
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.
PA1
Python-Data-Structures-py4e
learning excercise
python-for-everybody
PengxiangZhou98Whu's Repositories
PengxiangZhou98Whu/algo-dictionary
PengxiangZhou98Whu/bilibili-API-collect
哔哩哔哩-API收集整理【不断更新中....】
PengxiangZhou98Whu/Coursera-ML-AndrewNg-Notes
吴恩达老师的机器学习课程个人笔记
PengxiangZhou98Whu/cvx_short_course
Materials for a short course on convex optimization.
PengxiangZhou98Whu/datastructs_and_algorithm
Data struct and algorithm introduction and implementation in C/C++/Java.
PengxiangZhou98Whu/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.
PengxiangZhou98Whu/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.
PengxiangZhou98Whu/PA1
PengxiangZhou98Whu/Python-Data-Structures-py4e
learning excercise
PengxiangZhou98Whu/python-for-everybody
PengxiangZhou98Whu/Python-programming-for-everybody-py4e
PengxiangZhou98Whu/Python-Using-database-with-python-py4e
PengxiangZhou98Whu/Using-Python-to-Access-Web-Data--py4e