Source: DeepHub IMBA This article is about 3000 words long and is recommended to read in 6 minutes. With the latest advancements in NLP (Natural Language Processing), OpenAI's GPT-3 has become one of the most powerful language models on the market. On January 25, 2022, OpenAI announced an embedding endpoint (Neelakantan et al., 2022). This … Read more
When it comes to word vector models, many people’s first reaction is word2vec. In fact, the family of word vectors has many interesting members that differ in style from word2vec. At the same time, there are many improvements on top of word2vec. Here, I will briefly take you through these interesting word vector models in … Read more
Follow the official account “ML_NLP“ Set as “Starred“, receive heavy content promptly! Selected by | Ahmed BESBES Author | Ahmed Besbes Transferred from | Machine Heart This article introduces 7 models for text classification tasks, including traditional bag-of-words models, recurrent neural networks, convolutional neural networks commonly used in computer vision tasks, and RNN + CNN. … Read more
For all source code in this tutorial, please visit Github: https://github.com/zlsdu/Word-Embedding 1. Word2vec 1. Gensim Library The gensim library provides implementations of the Word2vec cbow model and skipgram model, which can be called directly. Full reference code 2. TensorFlow Implementation of Skipgram Model The skipgram model predicts context words based on a center word; there … Read more
Selected from arXiv Authors:Eric Wallace et al. Translation by Machine Heart Contributors:Mo Wang Performing numerical reasoning on natural language text is a long-standing challenge for end-to-end models. Researchers from the Allen Institute for AI, Peking University, and the University of California, Irvine, attempt to explore whether “out-of-the-box” neural NLP models can solve this problem, and … 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
Excerpt from Sebastian Ruder Blog Author: Sebastian Ruder Translated by: Machine Heart Contributors: Terrence L This article is Part 3 of the Word Embedding Series, introducing the popular word embedding model Global Vectors (GloVe). To read Part 2, click on Technical | Word Embedding Series Part 2: Comparing Several Methods of Approximate Softmax in Language … Read more
Follow the public account “ML_NLP“ Set as “Starred“, heavy content delivered to you first! Reprinted from: Machine Learning Beginner 0. Introduction Word embeddings refer to a set of language models and representation learning techniques in Natural Language Processing (NLP). Conceptually, it involves embedding a high-dimensional space of the number of words into a much lower-dimensional … Read more
Author: JayLou, NLP Algorithm Engineer Zhihu Column: High Energy NLP Journey This article is authorized, click “Read the original” at the end: https://zhuanlan.zhihu.com/p/56382372 This article summarizes word vectors in natural language processing in a Q&A format: including Word2Vec, GloVe, FastText, ELMo, and BERT. Table of Contents 1. Text Representation and Comparison of Word Vectors 1. … Read more