314 Open source projects that are alternatives of or similar to character-level-cnn

A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard.

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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.

Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.

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This repo contains a PyTorch implementation of a pretrained BERT model for text classification.

这是一款基于web的通用文本标注工具，支持大规模实体标注、关系标注、事件标注、文本分类、基于字典匹配和正则匹配的自动标注以及用于实现归一化的标准名标注，同时也支持文本的迭代标注和实体的嵌套标注。标注规范可自定义且同类型任务中可“一次创建多次复用”。通过分级实体集合扩大了实体类型的规模，并设计了全新高效的标注方式，提升了用户体验和标注效率。此外，本工具增加了审核环节，可对多人的标注结果进行一致性检验和调整，提高了标注语料的准确率和可靠性。

Indonesian twitter dataset for emotion classification task

Hierarchical Attention Networks | a PyTorch Tutorial to Text Classification

This repo contains a PyTorch implementation of a pretrained ERNIE model for text classification.

Text vectorization tool to outperform TFIDF for classification tasks

all kinds of baseline models for long text classificaiton( text categorization)

CNN for Chinese Text Classification in Tensorflow

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"20 newsgroups" dataset - Text Classification using Multinomial Naive Bayes in Python.

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基于scikit-learn实现对新浪新闻的文本分类，数据集为100w篇文档，总计10类，测试集与训练集1:1划分。分类算法采用SVM和Bayes，其中Bayes作为baseline。

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An experiment about re-implementing supervised learning models based on shallow neural network approaches (e.g. fastText) with some additional exclusive features and nice API. Written in Python and fully compatible with Scikit-learn.

Source code for the EMNLP 2020 paper "Cold-Start and Interpretability: Turning Regular Expressions intoTrainable Recurrent Neural Networks"

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A Python package implementing a new machine learning model for text classification with visualization tools for Explainable AI

A tutorial & minimal example (8min on CPU) for Graph Convolutional Networks for Text Classification. AAAI 2019

HDLTex: Hierarchical Deep Learning for Text Classification

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fastNLP: A Modularized and Extensible NLP Framework. Currently still in incubation.

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A text analyzer which is based on machine learning,statistics and dictionaries that can analyze text. So far, it supports hot word extracting, text classification, part of speech tagging, named entity recognition, chinese word segment, extracting address, synonym, text clustering, word2vec model, edit distance, chinese word segment, sentence similarity,word sentiment tendency, name recognition, idiom recognition, placename recognition, organization recognition, traditional chinese recognition, pinyin transform.

The aim of this repository is to show a baseline model for text classification by implementing a LSTM-based model coded in PyTorch. In order to provide a better understanding of the model, it will be used a Tweets dataset provided by Kaggle.

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Pedestrian Detection using Non Maximum Suppression

Very deep CNN for text classification

a small collection of models implemented in keras, including matrix factorization(recommendation system), topic modeling, text classification, etc. Runs on tensorflow.

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