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An Open-source Neural Hierarchical Multi-label Text Classification Toolkit
Text Mining and Topic Modeling Toolkit for Python with parallel processing power
Scikit-Learn, NLTK, Spacy, Gensim, Textblob and more
Code and preprocessed dataset for EMNLP 2019 paper titled "Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks"
[KBS] Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks
SenticNet / Sentic-GCN
Forked from BinLiang-NLP/Sentic-GCNAspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks. Knowledge-Based Systems (KBS)
Aspect Based Sentiment Analysis
Sentiment Analysis, Text Classification, Text Augmentation, Text Adversarial defense, etc.;
Zhuang Chen, Tieyun Qian: Relation-Aware Collaborative Learning for Unified Aspect-Based Sentiment Analysis. ACL 2020: 3685-3694
Open-Domain Targeted Sentiment Analysis via Span-Based Extraction and Classification
Code for "A Dependency Syntactic Knowledge Augmented Interactive Architecture for End-to-End Aspect-based Sentiment Analysis" on Neurocomputing.
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
[EMNLP 2019 Workshop] Exploiting BERT for End-to-End Aspect-based Sentiment Analysis
A privacy-first, open-source platform for knowledge management and collaboration. Download link: http://github.com/logseq/logseq/releases. roadmap: http://trello.com/b/8txSM12G/roadmap
Covid-19 Twitter dataset for non-commercial research use and pre-processing scripts - under active development
🍭在线工具秘籍,为在线工具写一本优质说明书,让在线工具造福人类~ Online tool cheats, write a quality manual for online tools, make online tools benefit humanity~
Now we have become very big, Different from the original idea. Collect premium software in various categories.
Dataountain疫情期间网民情绪识别比赛
Apache Superset is a Data Visualization and Data Exploration Platform
Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Advanced Deep Learning with Keras, published by Packt
整理一些书籍 ,包含 C&C++ 、git 、Java、Keras 、Linux 、NLP 、Python 、Scala 、TensorFlow 、大数据 、推荐系统、数据库、数据挖掘 、机器学习 、深度学习 、算法等。