word2vec

Machine learning, in numpy

大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP

Extract Keywords from sentence or Replace keywords in sentences.

Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.

Python interface to Google word2vec

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

Pre-trained word vectors of 30+ languages

Beautiful visualizations of how language differs among document types.

兜哥出品 <一本开源的NLP入门书籍>

A fast, efficient universal vector embedding utility package.

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

Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation)，etc. All codes are implemented intensorflow 2.0.

🦆 Contextually-keyed word vectors

Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano

Starter code to solve real world text data problems. Includes: Gensim Word2Vec, phrase embeddings, Text Classification with Logistic Regression, word count with pyspark, simple text preprocessing, pre-trained embeddings and more.

基于Pytorch和torchtext的自然语言处理深度学习框架。

Fast vectorization, topic modeling, distances and GloVe word embeddings in R.

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

A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017).

CS224n: Natural Language Processing with Deep Learning Assignments Winter, 2017

Deep neural network framework for multi-label text classification

中文詞向量訓練教學

Keras, PyTorch, and NumPy Implementations of Deep Learning Architectures for NLP

Multiple implementations for abstractive text summurization , using google colab

Fast word vectors with little memory usage in Python

Programming Assignments and Lectures for Stanford's CS 224: Natural Language Processing with Deep Learning

word2vec, sentence2vec, machine reading comprehension, dialog system, text classification, pretrained language model (i.e., XLNet, BERT, ELMo, GPT), sequence labeling, information retrieval, information extraction (i.e., entity, relation and event extraction), knowledge graph, text generation, network embedding

Vector Hub - Library for easy discovery, and consumption of State-of-the-art models to turn data into vectors. (text2vec, image2vec, video2vec, graph2vec, bert, inception, etc)

Python package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"