Four word embedding models implemented in Python. Supporting arbitrary context features

自然语言处理（NLP）教程，包括：词向量，词法分析，预训练语言模型，文本分类，文本语义匹配，信息抽取，翻译，对话。

Pre-trained models and language resources for Natural Language Processing in Polish

One-Stop Solution to encode sentence to fixed length vectors from various embedding techniques

Improved Word Representation Learning with Sememes

TensorFlow Implementation of the paper "End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures" and "Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths" for classifying relations

Word Embedding + LSTM + FC

Deep contextualized word representations for Chinese

Code & data accompanying the KDD 2017 paper "KATE: K-Competitive Autoencoder for Text"

Official Code Repository for LM-Steer Paper: "Word Embeddings Are Steers for Language Models" (ACL 2024 Outstanding Paper Award)

🗺️ 一个自然语言处理的学习路线图

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

Dead simple games made with word vectors.

Expose a Top2Vec model with a REST API.

MirasText

Library for Korean morpheme and word vector representation

Sequence Models by Andrew Ng on Coursera. Programming Assignments and Quiz Solutions.

Topical Word Embeddings

Revised Version of SAT Model in "Improved Word Representation Learning with Sememes"

A sparsity aware implementation of "Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence" (ICASSP 2014).

Superfast CUDA implementation of Word2Vec and Latent Dirichlet Allocation (LDA)

Code for the paper "A Multi-lingual Multi-task Architecture for Low-resource Sequence Labeling" (ACL2018)

Word Embeding with CNN

Word Embeding with Simple model, w2v, Simple RNN, LSTM

Geometry-aware Multilingual Embeddings

An Indonesian word embedding demo

The SINr approach to train interpretable word and graph embeddings

This repository consists of customized word embedding focused on banking and finance terms which will be helpful in analyzing and classifying financial sentiments or stock price sentiment analysis.

Analysis of DNA Sequence Classification Using Neural Networks - Bioinformatics Course Project - Winter 2022

Sequence Models repository for all projects and programming assignments of Course 5 of 5 of the Deep Learning Specialization offered on Coursera and taught by Andrew Ng, covering topics such as Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU), Long Short Term Memory (LSTM), Natural Language Processing, Word Embeddings and Attention Model.