Author: Dhruvil Karani Compiled by: ronghuaiyang Introduction This article introduces some basic concepts of word embeddings and Word2Vec. It is very straightforward and easy to understand. Word embeddings are one of the most common representations of a document’s vocabulary. They can capture the context, semantics, and syntactic similarities of a word in a document, as … Read more
word2vec Word2Vec is a model used to generate word vectors. These models are shallow, two-layer neural networks trained to reconstruct linguistic word texts.The network represents words and needs to predict the input words in adjacent positions. In Word2Vec, under the bag-of-words model assumption, the order of words is not important. After training, the Word2Vec model … Read more
Author：louwill From：Deep Learning Notes The language model is one of the core concepts in natural language processing. Word2Vec is a language model based on neural networks, and it is also a vocabulary representation method. Word2Vec includes two structures: skip-gram and CBOW (Continuous Bag of Words), but essentially both are a dimensionality reduction operation on vocabulary. … Read more
1 Meaning of Word2Vec A word cannot be understood by a neural network; it needs to be converted into numbers before being fed into it. The most naive way is one-hot encoding, but it is too sparse and not effective. So we improve it by compressing one-hot into a dense vector. The word2vec algorithm predicts … Read more
Follow the public account “ML_NLP“ Set as “Starred“, heavy content delivered to you first! Source | Zhihu Address | https://www.zhihu.com/question/44832436/answer/266068967 Author | crystalajj Editor | Machine Learning Algorithms and Natural Language Processing Public Account This article is for academic sharing only. If there is an infringement, please contact the background for deletion. Introduction How does … Read more
Deep Learning Author: louwill From: Deep Learning Notes Language models are one of the core concepts in natural language processing. Word2Vec is a language model based on neural networks and a method for word representation. Word2Vec includes two structures: skip-gram (Skip-gram Model) and CBOW (Continuous Bag of Words Model), both essentially perform dimensionality reduction on … Read more
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