[NeurIPS'23] Disentangling Cognitive Diagnosis with Limited Exercise Labels

EdNet is the dataset of all student-system interactions collected over 2 years by Santa, a multi-platform AI tutoring service with more than 780K users in Korea available through Android, iOS and web.

Advances on machine learning of graphs, covering the reading list of recent top academic conferences.

Code and data for "Do Models of Mental Health Based on Social Media Data Generalize?" appearing in Findings of EMNLP (2020)

Hierarchical Attention Network for Explainable Depression Detection on Twitter

Hierarchical Attention Network for Explainable Depression Detection on Twitter

Dataset for "Depression Detection via Harvesting Social Media: A Multimodal Dictionary Learning Solution" in IJCAI 17

An evolving list of electronic media data sets used to model mental-health status.

A unified framework for machine learning with time series

100+ Chinese Word Vectors 上百种预训练中文词向量

这个是一个《电商标题数据相似度匹配系统》，使用方法有：tfidf+词袋模型，余弦相似度，word2vec

中文文本分类 传统机器学习+深度学习

AI100文本分类竞赛代码。从传统机器学习到深度学习方法的测试

A Benchmark of Text Classification in PyTorch

Implemention some Baseline Model upon Bert for Text Classification

中文长文本分类、短句子分类、多标签分类、两句子相似度（Chinese Text Classification of Keras NLP, multi-label classify, or sentence classify, long or short），字词句向量嵌入层（embeddings）和网络层（graph）构建基类，FastText，TextCNN，CharCNN，TextRNN,…

中文文本分类，TextCNN，TextRNN，FastText，TextRCNN，BiLSTM_Attention，DPCNN，Transformer，基于pytorch，开箱即用。

all kinds of text classification models and more with deep learning

Library for fast text representation and classification.

codes for the IJCAI 2022 paper "Psychiatric Scale Guided Risky Post Screening for Early Detection of Depression"

Build your neural network easy and fast, 莫烦Python中文教学

Implementation of State-of-the-art Text Classification Models in Pytorch

使用pytorch搭建textCNN实现中文文本分类

DepressionEmo: A novel dataset for multilabel classification of depression emotions

Baseline scripts for AVEC 2019, Depression Detection Sub-challenge

This consists in using a variety of social networks data, including both images and texts, to detect early signs of depression.

This repository contains the code of our winning solution for the Shared Task on Detecting Signs of Depression from Social Media Text at LT-EDI-ACL2022.

The aim of this project is to predict whether a person is depressed or not using different machine learning algorithms based on the tweets of the user.