1587causalai Goto Github PK

aboutcausalai

This is an Introduction to Causal AI

ai-deadlines

:alarm_clock: AI conference deadline countdowns

ateam

A pyTorch Extension for Applied Mathematics

awesome-causal-chatgpt

Awesome Causal ChatGPT

awesome-causality-algorithms

An index of algorithms for learning causality with data

awesome-causality-data

A data index for learning causality.

causal-learn

Causal Discovery for Python. Translation and extension of the Tetrad Java code.

causalml

A course on causal machine learning.

causalml-data

Uplift modeling and causal inference with machine learning algorithms

code-of-learn-deep-learning-with-pytorch

This is code of book "Learn Deep Learning with PyTorch"

colossalai

Making large AI models cheaper, faster and more accessible

convex-optim-with-r

Convex optimization with R 的论文研读笔记

cruiser

混沌巡洋舰博客测试版

cs231

This the learning process for Standford CS231

datasharing

The Leek group guide to data sharing

debug-upgrade

It is the opportunity to upgrade my ability of using computer. It is the project of being a hack!

decisiontree

《机器学习》周志华（西瓜书）的决策树，实现了决策树的构建、可视化及预测。

discoreg

dl-4-tsc

Deep Learning for Time Series Classification

dlcv_for_beginners

《深度学习与计算机视觉》配套代码

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.

estcondmin

estcondmin-research

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

exdata_plotting1

Plotting Assignment 1 for Exploratory Data Analysis

gan_basic_example

gong-pkg

gongfunc

heyanggong.github.io