rsanshierli's starred repositories
kg-baseline-pytorch
2019百度的关系抽取比赛,使用Pytorch实现苏神的模型,F1在dev集可达到0.75,联合关系抽取,Joint Relation Extraction.
USC-DS-RelationExtraction
Distantly Supervised Relation Extraction
God-Of-BigData
专注大数据学习面试,大数据成神之路开启。Flink/Spark/Hadoop/Hbase/Hive...
Top-AI-Conferences-Paper-with-Code
MLNLP: This repository is a collection of AI top conferences papers (e.g. ACL, EMNLP, NAACL, COLING, AAAI, IJCAI, ICLR, NeurIPS, and ICML) with open resource code
bank_interview
:bank: 银行笔试面试经验分享及资料分享(help you pass the bank interview, and get a amazing bank offer!)
TextBrewer
A PyTorch-based knowledge distillation toolkit for natural language processing
transformers-tutorials
Github repo with tutorials to fine tune transformers for diff NLP tasks
fucking-algorithm
刷算法全靠套路,认准 labuladong 就够了!English version supported! Crack LeetCode, not only how, but also why.
nlp_xiaojiang
自然语言处理(nlp),小姜机器人(闲聊检索式chatbot),BERT句向量-相似度(Sentence Similarity),XLNET句向量-相似度(text xlnet embedding),文本分类(Text classification), 实体提取(ner,bert+bilstm+crf),数据增强(text augment, data enhance),同义句同义词生成,句子主干提取(mainpart),中文汉语短文本相似度,文本特征工程,keras-http-service调用
cail2019_track2
**法研杯CAIL2019要素抽取任务第三名方案分享
BERT-NER-Pytorch
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)
BERT-Vector
BERT预训练模型字向量提取工具
nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
spo_extract_platform
本项目是利用深度学习技术来构建知识图谱方向上的一次尝试,作为开放领域的关系抽取,算是笔者的一次创新,目前在这方面的文章和项目都很少。
EDA_NLP_for_Chinese
An implement of the paper of EDA for Chinese corpus.中文语料的EDA数据增强工具。NLP数据增强。论文阅读笔记。
Chinese-BERT-wwm
Pre-Training with Whole Word Masking for Chinese BERT(中文BERT-wwm系列模型)
team-learning
主要展示Datawhale的组队学习计划。
Your-first-machine-learning-Project---End-to-End-in-Python
这是一个完整的,端到端的机器学习项目,非常适合有一定基础后拿来练习,以提高对完整机器学习项目的认识
HarvestText
文本挖掘和预处理工具(文本清洗、新词发现、情感分析、实体识别链接、关键词抽取、知识抽取、句法分析等),无监督或弱监督方法
Multiple-Relations-Extraction-Only-Look-Once
Multiple-Relations-Extraction-Only-Look-Once. Just look at the sentence once and extract the multiple pairs of entities and their corresponding relations. 端到端联合多关系抽取模型,可用于 http://lic2019.ccf.org.cn/kg 信息抽取。
a_journey_into_math_of_ml
汉语自然语言处理视频教程-开源学习资料