Word embeddings represent a word with a numerical vector, which is different from the IDs used in Tokenization. Word embedding vectors carry more semantic information. This article will illustrate Word2Vec: a method for word embeddings. This series also includes illustrations of Tokenization, Transformer, GPT2, and BERT. If you want to learn about Tokenization, please see … Read more
Machine Learning Algorithms and Natural Language Processing Recommendations Source: https://zhuanlan.zhihu.com/p/58425003 Author: Xiao Chuan Ryan [Introduction to Machine Learning Algorithms and Natural Language Processing]BERT did not come out of nowhere; this article introduces some thoughts on how to derive it from Word2Vec! Recently, my work has been closely related to pre-trained models, but I found that … 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
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
Deep Learning Author: louwill From: Deep Learning Notes Language models are one of the core concepts in natural language processing. Word2Vec is a neural network-based language model and a method for word representation. Word2Vec includes two structures: skip-gram and CBOW (Continuous Bag of Words), but essentially both are operations for dimensionality reduction of vocabulary. Word2Vec … Read more
Reference Article: https://www.jianshu.com/p/471d9bfbd72f Before understanding word2vec, we first need to grasp what One-Hot encoding is, as this simple encoding method is quite useful for handling enumerable features. Encoding One-Hot encoding, also known as single valid encoding, uses an N-bit state register to encode N states, where each state has its own independent register bit, and … Read more
Follow the public account “ML_NLP” Set as “Starred”, heavy content delivered first time! Overview of this article: 1. Background Knowledge Word2Vec is a type of language model that learns semantic knowledge from a large amount of text data in an unsupervised manner, and is widely used in natural language processing. Word2Vec is a tool for … Read more
In enterprise practice, multiple OpenShift clusters are often deployed: for development testing, production, etc. Each cluster is independent and isolated by physical resources. This approach is simple to manage and easy to understand but consumes more resources, as each cluster requires additional control and operational nodes. Is there a way to run different environments on … Read more
This article is from the public account Silicon Star PeoplePro (ID: Si-Planet) Google’s large language model Gemini 1.0 has amazed everyone since its launch. In terms of performance, whether it is understanding text, images, and audio, or reasoning about texts in 57 fields and mathematical problems, it almost surpasses the dominant model in the natural … Read more
How to Obtain 1. Follow the public account below, and click 【Like】 and 【View】 in this article 2. Click 【Get Course】 in the public account to obtain this material There is a course on Basics of Machine Learning: Machine Learning and Materials/Chemistry Basics of Machine Learning: Machine Learning and Materials/Chemistry 1. Introduction to Machine Learning … Read more