Deep learning has opened a new chapter in machine learning, and currently, there have been groundbreaking research advances in deep learning applications in image and speech. Deep learning has long been praised as an artificial intelligence algorithm similar to the structure of the human brain. So why has there been no substantial progress in the … Read more
In today’s digital age, language processing technology is changing our lives and work at an unprecedented speed. From smart voice assistants to automatic translation software, from search engine optimization to sentiment analysis tools, the applications of natural language processing (NLP) are everywhere. Behind all this lies a key technology—the word vector model. Today, we will … Read more
After getting used to the operations of Word2Vec, today we will lift the lid and see what it’s really like inside. Word2Vec can transform words into vectors, which sounds quite magical, right? But once you understand the principle, you’ll find it’s just a little trick of assigning mathematical labels to words. Core Idea: Prediction Is … Read more
Introduction Remember not long ago in the field of machine reading comprehension, where Microsoft and Alibaba surpassed humans on SQuAD with R-Net+ and SLQA respectively, and Baidu topped the MS MARCO leaderboard with V-Net while exceeding human performance on BLEU? These networks can be said to be increasingly complex, and it seems that the research … Read more
Click the “Expert Knowledge” above to follow and get professional AI knowledge! ▌Introduction The traditional Vector Space Model (VSM) assumes that feature items are independent of each other, which does not align with reality. To address this issue, a distributed representation of text (e.g., in the form of word embeddings) can be employed, representing text … 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
Introduction References Main Content Dataset Model Training Model Evaluation Model Tuning Extensions Bonus Introduction Hello everyone, I am a dropout from Royal Bruster University of Data Mining, I drink the strongest orange juice and dig the deepest corners—persistent as I am. Last week, I impulsively dug a big pit of Word2vec, leaving the practical part … Read more
Li Zi from Ao Fei Si Quantum Bit | WeChat Official Account QbitAI Word2Vec is a language tool open-sourced by Google in 2013. A two-layer network can turn words into vectors, which is crucial in the NLP field and the foundation for many functionalities. However, now a programmer named bollu (short for Pineapple) loudly tells … Read more
Authorized by WeChat account Data Mining Machine Cultivation Diary Author | Mu Wen This article is exclusively authorized for reprint by “Big Data Digest” and prohibits all other forms of reprint without the author’s permission. Hello everyone, my name is Data Mining Machine, I dropped out of Royal Bruster University, I drink the strongest orange … Read more
The original article was published on the public account: A Confession of a Fortune-Telling Engineer. Feel free to follow at the end of the article to receive various reliable and unreliable updates from the author. Paper Title: Neural Word Embedding as Implicit Matrix Factorization This is an article from NIPS 2014, which is quite old. … Read more