Since Tomas Mikolov from Google proposed Word2Vec in “Efficient Estimation of Word Representation in Vector Space”, it has become a fundamental component of deep learning in natural language processing. The basic idea of Word2Vec is to represent each word in natural language as a short vector with a unified meaning and dimension. As for what … Read more
Author丨Tian Yu Su Zhihu Column丨Machine Learning Link丨https://zhuanlan.zhihu.com/p/27234078 1. Introduction This sharing mainly focuses on the translation, understanding, and integration of two English documents on the Word2Vec model, both of which introduce the Skip-Gram model in Word2Vec. The next column article will implement the basic version of the Word2Vec Skip-Gram model using TensorFlow, so this article … Read more
Author: Tian Yu Su Zhihu Column: Machine Learning Link: https://zhuanlan.zhihu.com/p/27234078 Before We Start The column has finally been approved, but I am currently applying for a name change, which may take a few days for review.In the future, I will periodically update the column with some content on machine learning and deep learning, mainly including … Read more
Source | Zhihu Author | TianMin Link丨https://zhuanlan.zhihu.com/p/85998950 Editor | Deep Learning Matters WeChat Official Account This article is for academic exchange only. If there is any infringement, please contact for removal. [Introduction] Word2Vec is a widely used word embedding method. Due to recent research needs, I studied the algorithm model. Since there is a lot … Read more
Reading time: approximately 5 minutes Follow the little blogger and improve a bit every day Author: gan Link: https://zhuanlan.zhihu.com/p/36312907 Background Introduction and Some Intuitive Understandings Word2Vec is a word vector model proposed by Google in 2012, which includes two models, Continuous Bag of Words (CBOW) and Skip Gram. The two models build word prediction models … Read more