100+ Chinese Word Vectors 上百种预训练中文词向量

A curated list of awesome embedding models tutorials, projects and communities.

A fast, efficient universal vector embedding utility package.

Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.

Implementation of triplet loss in TensorFlow

Pre-trained subword embeddings in 275 languages, based on Byte-Pair Encoding (BPE)

Curated list of 2vec-type embedding models

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

Named Entity Recognition using multilayered bidirectional LSTM

Library for faster pinned CPU <-> GPU transfer in Pytorch

A tool for learning vector representations of words and entities from Wikipedia

Code for the EMNLP-IJCNLP paper: Easy data augmentation techniques for boosting performance on text classification tasks.

Classify Kaggle Consumer Finance Complaints into 11 classes. Build the model with CNN (Convolutional Neural Network) and Word Embeddings on Tensorflow.

Fast word vectors with little memory usage in Python

Keras Implementations of Deep Learning Architectures for NLP

Implementation of the node2vec algorithm.

Curated List of Persian Natural Language Processing and Information Retrieval Tools and Resources

中文长文本分类、短句子分类、多标签分类、两句子相似度（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, Albert, Attention, DeepMoji, HAN, 胶囊网络-CapsuleNet, Transformer-encode, Seq2seq, ENT, DMN,

Natural Language Processing Pipeline - Sentence Splitting, Tokenization, Lemmatization, Part-of-speech Tagging and Dependency Parsing

PyTorch implementation of a deep metric learning technique called "Magnet Loss" from Facebook AI Research (FAIR) in ICLR 2016.

Making sense embedding out of word embeddings using graph-based word sense induction

Graph convolutional neural network for multirelational link prediction

cw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information

Representing research papers as vectors / latent representations.

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Chronic Disease Prediction Using Medical Notes

Code for the Recsys 2018 paper entitled Causal Embeddings for Recommandation.

Reasoning Over Knowledge Graph Paths for Recommendation