Continuous Bag of Words (CBOW)

意味表現学習

A word2vec port for Windows.

word to vector

Repository for the Google Deep Learning Course on Udacity.

How does Word2Vec work ?

This is the IR course of NTUST in 2017. IR means that Information Retrieval and Its Applications, including Vector Model, word2Vec technology and so on.

This is a practical implementation implementing neural networks on top of fasttext as well as word2vec word embeddings.

This repo is my implementation of the coding questions of assignment1 of Stanford University class: - [CS224n](cs224n.stanford.edu): Natural Language Processing with Deep Learning

My solutions to the class assignments

Implementation of CBOW and Skip-gram model in python

Learning to represent text using Word2Vec

Continuous Bag-of-Words (CBOW model implemented in pytorch

Word2Vec implementation in tensorflow

Recommender systems, 2017-18

Skip-gram, Cbow

Offline and online (i.e., real-time) annotated clustering methods for text data.

Neural sentiment classification of text using the Stanford Sentiment Treebank (SST-2) movie reviews dataset, logistic regression, naive bayes, continuous bag of words, and multiple CNN variants.

结合python一起学习自然语言处理 (nlp): 语言模型、HMM、PCFG、Word2vec、完形填空式阅读理解任务、朴素贝叶斯分类器、TFIDF、PCA、SVD

Text classification of Times of India articles on HIV-AIDS since 2010 using neural networks and web scraping using BeautifulSoup.