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ai-economist

Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).

ai-roadmap

ApacheCN AI 路线图（知识树）

annotated_deep_learning_paper_implementations

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

awesome-algorithm

刷题训练指南

awesome-causality-algorithms

An index of algorithms for learning causality with data

awesome-causality-data

A data index for learning causality.

awesome-fairness-in-ai

A curated list of awesome Fairness in AI resources

awesome-fairness-papers

Papers on fairness in NLP

bartpy

Bayesian Additive Regression Trees For Python

causal-network-embeddings

Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"

causal_inference_python_code

Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins

causality-fairness

References for Papers at the Intersection of Causality and Fairness

causallib

A Python package for modular causal inference analysis and model evaluations

cbps

R package: CBPS

cevae

Causal Effect Inference with Deep Latent-Variable Models

cevae_pytorch

cleaningdata

homwork

club

Code for ICML2020 paper - CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information

continuous-fairness

course-nlp

A Code-First Introduction to NLP course

course-v3

The 3rd edition of course.fast.ai

coursera-ibm-ai-engineering

IBM - AI Engineering Professional Certificate

coursera-math-for-ml-linear-algebra

Mathematics for Machine Learning: Linear Algebra - Coursera - Imperial College London

courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

cs229t

Statistical Learning Theory (CS229T) Lecture Notes

d2l-en

Dive into Deep Learning: an interactive deep learning book with code, math, and discussions

d2l-pytorch

This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

datasciencecoursera

datasharing

The Leek group guide to data sharing

ddz-ai

以孤立语假设和宽度优先搜索为基础，构建了一种多通道堆叠注意力Transformer结构的斗地主ai