581 Open source projects that are alternatives of or similar to Fancy Nlp

ATEC 金融大脑-金融智能NLP服务

An Efficient Lexical Analyzer for Chinese

An Efficient Chinese Text Classifier

Detecting Sarcasm on Twitter using both traditonal machine learning and deep learning techniques.

Natural Language Processing Best Practices & Examples

Named-Entity-Recognition-with-Bidirectional-LSTM-CNNs

TriggerNER: Learning with Entity Triggers as Explanations for Named Entity Recognition (ACL 2020)

RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.

Character-level Convolutional Networks for Text Classification论文仿真实现

modest natural-language processing

An Efficient Lexical Analyzer for Chinese

Empower Sequence Labeling with Task-Aware Neural Language Model | a PyTorch Tutorial to Sequence Labeling

基于 TensorFlow & PaddlePaddle 的通用序列标注算法库（目前包含 BiLSTM+CRF, Stacked-BiLSTM+CRF 和 IDCNN+CRF，更多算法正在持续添加中）实现中文分词（Tokenizer / segmentation）、词性标注（Part Of Speech, POS）和命名实体识别（Named Entity Recognition, NER）等序列标注任务。

ADEL is a robust and efficient entity linking framework that is adaptive to text genres and language, entity types for the classification task and referent knowledge base for the linking task.

对收集的法律文档进行一系列分析，包括根据规范自动切分、案件相似度计算、案件聚类、法律条文推荐等（试验目前基于婚姻类案件，可扩展至其它领域）。

Named Entities Recognition Annotator Tool for Europeana Newspapers

Bert-classification and bert-dssm implementation with keras.

A neural network layer that enables training of deep neural networks directly from crowdsourced labels (e.g. from Amazon Mechanical Turk) or, more generally, labels from multiple annotators with different biases and levels of expertise.

Text classification models implemented in Keras, including: FastText, TextCNN, TextRNN, TextBiRNN, TextAttBiRNN, HAN, RCNN, RCNNVariant, etc.

[CIKM 2018] Weakly-Supervised Neural Text Classification

Nodejs binding for fasttext representation and classification.

A bidirectional LSTM with attention for multiclass/multilabel text classification.

Machine Learning (EE 5184) in NTU

Edge-aware U-Net with CRF-RNN layer for Medical Image Segmentation

Keras solution of Chinese NER task using BiLSTM-CRF/BiGRU-CRF/IDCNN-CRF model with Pretrained Language Model: supporting BERT/RoBERTa/ALBERT

Implementing nlp papers relevant to classification with PyTorch, gluonnlp

Code for ACL '19 paper: Towards Improving Neural Named Entity Recognition with Gazetteers

sentiment analysis、文本分类、ALBERT、TextCNN、classification、tensorflow、BERT、CNN、text classification

HDLTex: Hierarchical Deep Learning for Text Classification

Embedding, NMT, Text_Classification, Text_Generation, NER etc.

Chinese & English Cws Pos Ner Entity Recognition implement using CNN bi-directional lstm and crf model with char embedding.基于字向量的CNN池化双向BiLSTM与CRF模型的网络，可能一体化的完成中文和英文分词，词性标注，实体识别。主要包括原始文本数据，数据转换,训练脚本,预训练模型,可用于序列标注研究.注意：唯一需要实现的逻辑是将用户数据转化为序列模型。分词准确率约为93%，词性标注准确率约为90%，实体标注（在本样本上）约为85%。

Official Stanford NLP Python Library for Many Human Languages

This case study shows how to create a model for text analysis and classification and deploy it as a web service in Azure cloud in order to automatically classify support tickets. This project is a proof of concept made by Microsoft (Commercial Software Engineering team) in collaboration with Endava http://endava.com/en

Arabic support for textblob

Stanford Named Entity Recognizer (NER) - Python Wrapper

Open-source benchmark datasets and pretrained transformer models in the Filipino language.

Framework to learn Named Entity Recognition models without labelled data using weak supervision.

Multi-Task Deep Neural Networks for Natural Language Understanding

Evidence-based Explanation Dataset (AACL-IJCNLP 2020)

A Modern C++ Data Sciences Toolkit

BAND：BERT Application aNd Deployment，Simple and efficient BERT model training and deployment, 简单高效的 BERT 模型训练和部署

DELTA is a deep learning based natural language and speech processing platform.

An open source library for deep learning end-to-end dialog systems and chatbots.

Transition-based NER system

Educational material on using the TensorFlow Estimator framework for text classification

🍀 Another Chinese chatbot implemented in PyTorch, which is the sub-module of intelligent work order processing robot. 👩‍🔧

The missing SVM-based text classification module implementing HanLP's interface

A Python interface for Facebook fastText

No description or website provided.

A frame-semantic parsing system based on a softmax-margin SegRNN.

The CRF Layer was implemented by using Chainer 2.0. Please see more details here: https://createmomo.github.io/2017/09/12/CRF_Layer_on_the_Top_of_BiLSTM_1/

Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.

Classify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN (GRU and LSTM) and Word Embeddings on Tensorflow.

R wrapper for fastText

The Python Code Tutorials

Multi-label Classification with BERT; Fine Grained Sentiment Analysis from AI challenger

Python/Django based webapps and web user interfaces for search, structure (meta data management like thesaurus, ontologies, annotations and named entities) and data import (ETL like text extraction, OCR and crawling filesystems or websites)

Based on the Pytorch-Transformers library by HuggingFace. To be used as a starting point for employing Transformer models in text classification tasks. Contains code to easily train BERT, XLNet, RoBERTa, and XLM models for text classification.

NLP Core Library and Model Zoo based on PaddlePaddle 2.0