Submission by Machine Heart Author: Tang Zhengyang The author of this article, Tang Zhengyang, is the Market Manager at CreditX. He provides a clear introduction to the deep learning technology Word2vec and its applications in the field of financial risk control. In the current more inclusive market environment, the customer base and scope of new … Read more
A crucial step in training a chatbot is word vector training. Whether it’s a generative chatbot or a retrieval-based chatbot, it is necessary to convert text into word vectors. The most popular word vector training model nowadays is Word2Vec. Today, I will guide you through training word vectors using Chinese Wikipedia. Training Data Download We … 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 on the “AI Youdao” above to select the “Top” public account Heavyweight content delivered first-hand This article is reproduced from Big Data Digest, secondary reproduction is prohibited Translated by Zhang Qiuyue, Yihang, Gao Yan, Long Xincheng Embedding is one of the most fascinating ideas in machine learning. If you have ever used Siri, Google … 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
Technical Column Author: Yang Hangfeng Editor: Zhang Nimei 1.Word2Vec Overview Word2Vec is simply a method of representing the semantic information of words through learning from text and using word vectors, that is, mapping the original word space to a new space through Embedding, so that semantically similar words are close to each other in this … 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 Introduction This article mainly introduces a very classic algorithm in word embedding, Word2Vec. Initially, Word2Vec was primarily used in text-related problems, but now friends participating in competitions should have noticed that almost half of the traditional data competitions involve Word2Vec. Therefore, we must take a good look at what Word2Vec is actually learning, so … 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
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