This article is reprinted with permission from the WeChat official account Paper Weekly (ID: paperweekly). Paperweekly shares interesting papers in the field of natural language processing every week. Introduction Dialogue systems are currently a hot research topic and a hotspot for venture capital. Since early 2016, countless companies have been established to create chatbots, voice … Read more
Follow our WeChat public account “ML_NLP“ Set as “Starred“, heavy content delivered to you instantly! Reprinted from｜PaperWeekly ©PaperWeekly Original · Author｜ Su Jianlin Unit｜Zhuiyi Technology Research Direction｜NLP, Neural Networks ▲ The Years of “Chicken and Rabbit in the Same Cage” “Profit and Loss Problems”, “Age Problems”, “Tree Planting Problems”, “Cows Eating Grass Problems”, “Profit Problems”… … Read more
Source: Deephub Imba This article is about 1500 words long and takes about 5 minutes to read. In this article, we want to demonstrate how to use the pre-trained weights of an encoder-only model to provide a good starting point for our fine-tuning. BERT is a famous and powerful pre-trained encoder model. Let’s see how … Read more
Chatbot Practice A chatbot is a computer program designed to simulate human conversation or chat, essentially enabling machines to understand human language through technologies like machine learning and artificial intelligence. It integrates methods from various disciplines and serves as a concentrated training camp in the field of artificial intelligence. In the coming decades, the way … Read more
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
Click the above“Beginner Learning Visuals” to selectStar or “Pin” Important content delivered promptly Generation of Attention Reason:《Sequence to Sequence Learning with Neural Networks》 Reason for introducing Attention model: Seq2seq compresses the input sequence into a fixed-size hidden variable, similar to our compressed files. This process is lossy and forces the loss of much information from … Read more
Click the top “MLNLP” to select the “Starred” public account. Heavyweight content delivered first-hand. From:Number Theory Legacy The prerequisite knowledge for this article includes:Recurrent Neural NetworksRNN, Word EmbeddingsWordEmbedding, Gated UnitsVanillaRNN/GRU/LSTM. 1 Seq2Seq Seq2Seq is the abbreviation for sequence to sequence. The first sequence is called the encoder encoder, which is used to receive the source … 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
Source: Deephub Imba This article has a total of 2700 words, recommended reading time is 5 minutes. This article will give you an understanding of the overall architecture of the Transformer. For many years, deep learning has been continuously evolving. Deep learning practice emphasizes the use of a large number of parameters to extract useful … Read more
©PaperWeekly Original · Author｜Su Jianlin Unit｜Zhuiyi Technology Research Direction｜NLP, Neural Networks ▲ The Years of “Chickens and Rabbits in the Same Cage” “Profit and loss problems”, “age problems”, “planting trees problems”, “cows eating grass problems”, “profit problems”… Have you ever been tormented by various types of math word problems during elementary school? No worries, machine … Read more