Follow us on WeChat: ML_NLP. Set as a “Starred” account for heavy content delivered to you first! Source: | Zhihu Link: | https://zhuanlan.zhihu.com/p/40920384 Author: | Yuanche.Sh Editor: | Machine Learning Algorithms and Natural Language Processing WeChat account This article is for academic sharing only. If there is any infringement, please contact us to delete it. … Read more
Author丨Fat Cat, Yi Zhen Zhihu Column丨Machine Learning Algorithms and Natural Language Processing Address丨https://zhuanlan.zhihu.com/p/82477941 Natural Language Processing (NLP) is generally divided into two categories: Natural Language Understanding (NLU) and Natural Language Generation (NLG). The former extracts or analyzes concise logical information from a piece of text, such as Named Entity Recognition (NER) which identifies keywords in … Read more
Source:Zhuanzhi This article is a multi-resource, recommended reading in 5 minutes. This article details the Attention model‘s concept, definition, impact, and how to get started with practical work. [Introduction]The Attention model has become an important concept in neural networks, and this article brings you the latest overview of this model, detailing its concept, definition, impact, … Read more
Author丨Tianyu Su Zhihu Column丨Machines Don’t Learn Address丨https://zhuanlan.zhihu.com/p/27769286 In the previous column, we implemented a basic version of the Seq2Seq model. This model performs sorting of letters, taking an input sequence of letters and returning the sorted sequence. Through the implementation in the last article, we have gained an understanding of the Seq2Seq model, which mainly … Read more
Author: Chen Zhi Yan This article is approximately 3500 words long and is recommended for a 7-minute read. The Transformer is the first model that completely relies on the self-attention mechanism to compute its input and output representations. The mainstream sequence-to-sequence models are based on encoder-decoder recurrent or convolutional neural networks. The introduction of the … Read more
In the previous lecture, we discussed the seq2seq model. Although the seq2seq model is powerful, its effectiveness can be significantly reduced if used in isolation. This section introduces the attention model, which simulates the human attention intuition within the encoder-decoder framework. Principle of Attention Mechanism The attention mechanism in the human brain is essentially a … Read more
In the previous article, we learned about the basic seq2seq model, which processes the input sequence through an encoder, passes the calculated hidden state to a decoder, and then decodes it to obtain the output sequence. The block diagram is shown again below: The basic seq2seq model is quite effective for short and medium-length sentences … Read more
The author of this article – Teacher Tom ▷ Doctorate from a double first-class domestic university, national key laboratory ▷ Published 12 papers at top international conferences, obtained 2 national invention patents, served as a reviewer for multiple international journals ▷ Guided more than ten doctoral and master’s students Research Areas: General visual-language cross-modal model … Read more
Selected from TowardsDataScience Author: Raimi Karim Contributors: Gao Xuan, Lu This article visually explains the attention mechanism with several animated diagrams and shares four NMT architectures that have emerged in the past five years, along with intuitive explanations of some concepts mentioned in the text. For decades, statistical machine translation has dominated translation models [9], … Read more
Selected from arXiv Author: Graham Neubig Translation by Machine Heart Contributors: Li Zenan, Jiang Siyuan This article is a detailed tutorial on machine translation, suitable for readers with a background in computer science. According to Paper Weekly (ID: paperweekly), this paper comes from CMU LTI and covers various foundational knowledge of the Seq2Seq method, including … Read more