isunym Goto Github PK

aaai18-code

The code of AAAI18 paper "Learning Structured Representation for Text Classification via Reinforcement Learning".

allennlp

An open-source NLP research library, built on PyTorch.

bank_interview

:bank: 银行笔试面试经验分享及资料分享（help you pass the bank interview, and get a amazing bank offer!）

bert

TensorFlow code and pre-trained models for BERT

bert-as-service

Mapping a variable-length sentence to a fixed-length vector using BERT model

bert-textclassification

bert-thucnews

bilm-tf

Tensorflow implementation of contextualized word representations from bi-directional language models

capsulenetforsentenceclassification

init

char-cnn-text-classification-pytorch

Character-level Convolutional Neural Networks for text classification in PyTorch

charcnn

cnn_multilabel_classification

Multilabel classification based on TextCNN and Attention

crowdlayer

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.

dan

Deep Averaging Networks

deeplearningfortextclassification

deep learning model for text classification

dpcnn

Deep Pyramid Convolutional Neural Networks for Text Categorization in PyTorch

dsn

Pytorch implementation of Domain Separation Networks

fudan_mtl_reviews

TensorFlow implementation of the paper `Adversarial Multi-task Learning for Text Classification`

it4866

Use LDA to classify 20newsgroup

jmars

Jointly Modelling Aspects, Ratings and Sentiments for Movie Recommendation (JMARS)

keras-textclassification

中文长文本分类、短句子分类、多标签分类（Chinese Text Classification of Keras NLP, multi-label classify, or sentence classify, long or short），字词句向量嵌入层（embeddings）和网络层（graph）构建基类，FastText，TextCNN，CharCNN，TextRNN, RCNN, DCNN, DPCNN, VDCNN, CRNN, Bert, Xlnet, Attention, DeepMoji, HAN, 胶囊网络-CapsuleNet, Transformer-encode, Seq2seq, ENT, DMN,

lda_papers

Latent Dirchilet Allocation for classifying scientific papers through topic modelling

leam

ma-sldac

Multi-Annotator Supervised LDA for classification

selfattentivesentembed

Source code for ``A Structured Self-Attentive Sentence Embedding'' published in ICLR 2017

sentencesentimentclassifier

Sentiment Classifier base on traditional Maching learning methods, eg Bayes, SVM ,DecisionTree, KNN and Deeplearning method like MLP,CNN,RNN(LSTM). 基于机器学习与深度学习方法的情感分析算法实现与对比，包括决策树，贝叶斯，KNN, SVM ,MLP, CNN, LSTM实现

sentiment-based-document-classification

Implementation of Language Model classifier, Perceptron classifier and SVM classifier to classify documents based on the sentiments of the text

sentimentanalysis

The code learns Support Vector Machines using 'linear' kernel to classify test data. Scikit-learn's LinearSVC provides a fast implementation for linear kernel SVMs. The features extracted from the text included the Tf-idf matrix, a commonly used method to convert text into a vetor space. Scikit-learn;s TfidVectorizer provides a complete and convenient set of functions for this. In addition to this, TruncatedSVD, another class in scikit-learn is used to approximate the feature vectors to a lower dimension (100~500 dimensions). Applying various combinations of the the different parameters (including the slack variable C in SVM, principal component size in SVD truncation and usage of monograms or bigrams in the feature extraction stage) a best estimator was selected based on

structured-self-attention

A Structured Self-attentive Sentence Embedding

structured-self-attentive-sentence-embedding

This is an implementation of paper A-STRUCTURED-SELF-ATTENTIVE-SENTENCE-EMBEDDING by PyTorch.