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ai-learn

人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

albert_lstm_crf_ner

albert + lstm + crf实体识别，pytorch实现。识别的主要实体是人名、地名、机构名和时间。albert + lstm + crf (named entity recognition)

albert_ner

基于轻量级的albert实现albert+BiLstm+CRF

albert_ner_keras

基于albert_bilstm_crf架构利用keras框架实现NER。

aspect-extraction

Aspect extraction from product reviews - window-CNN+maxpool+CRF, BiLSTM+CRF, MLP+CRF

bert-bilstm-cnn-crf-ner

bert-bilstm-crf-for-ner

利用预训练Bert模型完成命名实体识别

bert-bilstm-idcnn-crf

BERT-BiLSTM-IDCNN-CRF Keras版实现

bert-crf-for-chinese-ner

Using BERT+CRF model to do Chinese NER task

bert-ner

BERT+BiLSTM+CRF or BERT+CRF

bert-ner-keras

Chinese NER task with BERT/roberta/macbert/bert_wwm for keras

bertner_legal_pretrained

使用了Pre-trained Chinese ELECTRA，bert+BiLSTM+CRF的法律文书命名实体识别，进行交通肇事案的事件要素抽取

bigru-crf-with-attention-for-ner

Named Entity Recognition (NER) with different combinations of BiGRU, Self-Attention and CRF

bilstm_crf

bilstm_crf 命名实体识别

blstm-crf-ner

BiLSTM+CNN+CRF NER, using pytorch

chinese-ner

中文命名实体识别

chinese-ner-1

bilstm _Attention_crf

chinese-ner-2

Chinese NER using BiLSTM/BERT + CRF

chinese-ner-pytorch

中文实体识别 bert/xlnet/albert ...预训练模型 +bilstm+crf / +crf

chinesener

基于Bi-GRU + CRF 的中文机构名、人名识别, 支持google bert模型

chinesener-1

中文命名实体识别，实体抽取，tensorflow，pytorch，BiLSTM+CRF

chinesener-pytorch

基于Pytorch的BERT-IDCNN-BILSTM-CRF中文实体识别实现

cluener2020

A PyTorch implementation of a BiLSTM\BERT\Roberta(+CRF) model for Named Entity Recognition.

cnn-lstm-crf

cnn bilstm crf 作中文命名实体识别

co-in

知识图谱定义及可视化系统&基于可编辑知识图谱的菜肴问答系统：构建一个能通过在线编辑基本图元，以可视化的方式构建知识图谱的系统 平台，并能对构建后的知识图谱进行智能化知识图谱应用，实现知识图谱语义搜索、知识图谱智能问答等。

education_knowledge_graph_app

Education knowledge graph(graph display, knowledge point tracking, intelligent question and answer，questions knowledge point prediction)。k12教育学科知识图谱，图谱展示，知识点追踪，智能问答以及题目知识点预测。

entity-recognize

命名实体识别方法，毕设用

gan-bert-crf

An idea that take advantages of features of deep learning to use unannotated samples for NER and identify sequences with error labels.

information-extraction-chinese

Chinese Named Entity Recognition with IDCNN/biLSTM+CRF, and Relation Extraction with biGRU+2ATT 中文实体识别与关系提取

kb-qa

基于知识库的中文问答系统（biLSTM）