100 Questions on Deep Learning Author: louwill Machine Learning Lab The MobileNet series, as a representative of lightweight networks, makes the lightweight deployment of CNNs on mobile devices possible. Currently, there are three versions of MobileNet: MobileNet v1, MobileNet v2, and MobileNet v3. This article focuses on elaborating the MobileNet series networks, which is essential … Read more
RNNs, or Recurrent Neural Networks, are an important theoretical tool in both machine learning and computational neuroscience. In today’s world dominated by transformers, many may have forgotten about RNNs. However, RNNs remain a fundamental type of neural network and will surely play a role in the era of large models. First, let’s look at the … Read more
Selected from MachineLearningMastery Author: Jason Brownlee Translated by Machine Heart Contributors: Nurhachu Null, Lu Xue The encoder-decoder structure has shown advanced levels in several fields, but this structure encodes the input sequence into a fixed-length internal representation. This limits the length of the input sequence and results in poorer performance of the model on particularly … Read more
Follow the public account “ML_NLP“ Set as “Starred“, delivering heavyweight content to you first! Reprinted from | PaperWeekly ©PaperWeekly Original · Author｜Su Jianlin Unit｜Zhuiyi Technology Research Direction｜NLP, Neural Networks Although Transformer models have conquered most fields in NLP, RNN models like LSTM and GRU still hold unique value in certain scenarios, making it worthwhile for … Read more
Click the “MLNLP” above to select the “Star” public account Heavyweight content delivered first-hand From | Zhihu Author | Lucas Address | https://zhuanlan.zhihu.com/p/85995376 Column | Deep Learning and Sentiment Analysis Editor | Machine Learning Algorithms and Natural Language Processing Understanding RNN: Recurrent Neural Networks and Their Implementation in PyTorch Recurrent Neural Networks (RNN) are a … Read more
©PaperWeekly Original · Author | Su Jianlin Affiliation | Scientific Space Research Direction | NLP, Neural Networks In recent years, linear RNNs have attracted some researchers’ attention due to their characteristics such as parallel training and constant inference costs (for example, my previous article titled “Google’s New Work Attempts to ‘Revive’ RNN: Can RNN Shine … Read more
Author | Sandeep Bhupatiraju Translator | Liu Zhiyong Editor | Debra Chen AI Frontline Overview: Over a century ago, in the United States, people used Morse code to send the first telegram in human history, opening a new chapter for mankind. The advent of Morse code has had a profound and far-reaching impact on human … Read more
Author: David 9 Address: http://nooverfit.com/ RNN seems to be better at information preservation and updating, while CNN seems to excel at precise feature extraction; RNN has flexible input and output dimensions, while CNN dimensions are relatively rigid. 1Question When talking about Recurrent Neural Networks, our first reaction might be: time sequence. Indeed, RNNs are good … Read more
Recurrent Neural Networks (RNN) are designed based on the recursive nature of sequential data (such as language, speech, and time series) and are a type of feedback neural network that contains loops and self-repetitions, hence the name “recurrent”. They are specifically used to handle sequential data, such as generating text word by word or predicting … Read more
In an era flooded with fragmented reading, fewer people pay attention to the exploration and thinking behind each paper. In this column, you will quickly get the highlights and pain points of selected papers, keeping up with the forefront of AI achievements. Click the “Read Original” at the bottom of this article to join the … Read more