Author: Shivam Bansal Translated by: Shen Libin Proofread by: Ding Nanya This article is approximately 2300 words, and is recommended to be read in 8 minutes. This article will detail the text classification problem and implement this process in Python. Introduction Text classification is a common natural language processing task in business problems, with the … Read more
The application of Bert in production environments requires compression, which demands a deep understanding of the Bert structure. This repository will interpret the Bert source code (PyTorch version) step by step. The repository can be found at https://github.com/DA-southampton/NLP_ability Code and Data Introduction First, for the code, I referenced this repository. I directly cloned the code … Read more
Author: GjZero Tags: Bert, Chinese Classification, Sentence Vector This article is about 1500 words, recommended reading time is 8 minutes. This article starts from practice, guiding everyone through the tutorial on Chinese text classification using Bert and its use as a sentence vector. Bert Introduction The Bert model is a language representation model released by … Read more
Follow the public account “ML_NLP“ Set it as “Starred“, delivering heavy content to you first! Source | Zhihu Address | https://zhuanlan.zhihu.com/p/69389583 Author | Lao Song’s Tea Book Club 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 backend … Read more
Introduction to the Paper Despite the increasing applications of prompt learning methods in various few-shot natural language processing tasks, designing templates and label mappings in prompt learning is quite challenging, requiring a deep understanding of the model and classification tasks, along with extensive trial and error. Existing methods for automating label mapping design, while saving … Read more
Source: TsinghuaNLP, Deep Learning Natural Language Processing This article is about 2400 words long and is recommended to be read in 5 minutes. This article uses a knowledge base to expand and improve label words, achieving better text classification results. Background Using Prompt Learning for text classification tasks is an emerging method that leverages pre-trained … Read more
Ding Zhengsheng， Ma Chunjie （Xi’an University of Science and Technology， Shanxi Xi’an 710600） Abstract: In order to improve the efficiency and accuracy of Chinese text classification, a Chinese text classification algorithm based on deep learning is established in response to the characteristics of Chinese characters and the dramatic increase in data volume in the big … Read more
0 Introduction With the vigorous development of technologies such as the Internet, big data, and artificial intelligence, the new scientific revolution poses new opportunities and challenges for current engineering education in higher education institutions[1]. In 2017, the Ministry of Education actively promoted the construction of new engineering disciplines, striving to explore a Chinese model and … Read more
Introduction Natural Language Processing is a subfield of computer science, information engineering, and artificial intelligence, which involves the interaction between computers and human languages, processing and analyzing large amounts of natural language data through programming. 1Natural Language Processing(NLP) = Computer Science + AI + Computational Linguistics In other words, natural language processing is the ability … 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