Must-read papers on graph neural networks (GNN)

DHGNN source code for IJCAI19 paper: "Dynamic Hypergraph Neural Networks"

A pytorch library for graph and hypergraph computation.

Hypergraph Neural Networks (AAAI 2019)

Generate embeddings from large-scale graph-structured data.

A collection of important graph embedding, classification and representation learning papers with implementations.

Implementation and experiments of graph embedding algorithms.

coursera吴恩达机器学习课程作业自写Python版本+Matlab原版

Coursera Machine Learning (Andrew Ng) --- python code

吴恩达老师的机器学习课程个人笔记

吴恩达（Andrew Ng）在coursera的机器学习课程习题的python实现

A collection of machine learning examples and tutorials.

⚡机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归

机器学习算法python实现

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to G…

A list of NLP resources focused on event extraction task

A concept and obvious expression pattern collection of Chinese compound event extraction which then be evolved into ComplexEventGraph，本项目提出了中文复合事件的概念与显式模式，包括条件事件、因果事件、顺承事件、反转事件等事件抽取，并形成事理图谱。

An experiment and demo-level tool for text information extraction (event-triples extraction), which can be a route to the event chain and topic graph, 基于依存句法与语义角色标注的事件三元组抽取，可用于文本理解如文档主题链，事件线等应用。

2015年以来基于深度学习方法的事件抽取论文整理

近年来事件抽取方法总结，包括中文事件抽取、开放域事件抽取、事件数据生成、跨语言事件抽取、小样本事件抽取、零样本事件抽取等类型，DMCNN、FramNet、DLRNN、DBRNN、GCN、DAG-GRU、JMEE、PLMEE等方法

A comprehensive, unified and modular event extraction toolkit.

My Python Examples

All Algorithms implemented in Python