moxue's repositories
Agriculture_KnowledgeGraph
农业知识图谱(AgriKG)：农业领域的信息检索，命名实体识别，关系抽取，智能问答，辅助决策
economic_audit_knowledge_graph
经济责任审计知识图谱：网络爬虫、关系抽取、领域词汇判定
AES_DL
Automated Essay Scoring using BERT
AiLearning
AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
awesome-knowledge-graph
整理知识图谱相关学习资料
baidu_nlp_project2
开课吧&后厂理工学院_百度NLP项目2：试题数据集多标签文本分类 Models: FastText TextCNN GCN BERT et al.
CIKM-2019-AnalytiCup
1st Solution for 2019-CIKM-Analyticup, Efficient and Novel Item Retrieval for Large-scale Online Shopping Recommendation
DG-Net-PP
Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification. ECCV'20 (Oral)
eat_tensorflow2_in_30_days
Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋
fast-reid
SOTA Re-identification Methods and Toolbox
LeetCode-Python-Solution
solution of LeetCode by Python
manim
Animation engine for explanatory math videos
manim-tutorial-CN
manim中文教程,如果想系统地学习一些用法欢迎进入我的疫情期间搭建的博客
MEB-Net
"Multiple Expert Brainstorming for Domain Adaptive Person Re-identification", ECCV 2020
NLP-Models-Tensorflow
Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0
NLP-progress
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
NLPer-Interview
该仓库主要记录 NLP 算法工程师相关的面试题
PARL
A high-performance distributed training framework for Reinforcement Learning
RecBole
A unified, comprehensive and efficient recommendation library
RSPapers
Must-read papers on Recommender System.
Tianchi-AntaiCup-International-E-commerce-Artificial-Intelligence-Challenge
1st place solution for the AntaiCup-International-E-commerce-Artificial-Intelligence-Challenge
TianChi_ZhiLianZhaoPin
第二届阿里巴巴大数据智能云上编程大赛-智联招聘人岗智能匹配
transformers
🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.
tweet_sentiment_extraction
tweet sentiment extraction of kaggle competition
wechat_articles_spider
微信公众号的爬虫
xlearn
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.