Animated RNN, LSTM, and GRU Computation Process

Animated RNN, LSTM, and GRU Computation Process

Source | Zhihu Author | JerryFly Link | https://zhuanlan.zhihu.com/p/115823190 Editor | Deep Learning Matters WeChat Official Account This article is for academic exchange only. If there is any infringement, please contact us for deletion. RNN is commonly used to handle sequential problems. This article demonstrates the computation process of RNN using animated graphics. The three … Read more

From RNN/CNN to Large Models: A Comprehensive Analysis

From RNN/CNN to Large Models: A Comprehensive Analysis

“Programming is the art of telling another human being what one wants the computer to do.” — Donald Knuth 📑Paper:A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond 🔧GitHub:https://github.com/QiushiSun/NCISurvey Note: The authors of the paper are from Shanghai Artificial Intelligence Laboratory, The University of Hong Kong, National University of Singapore, East China Normal University, … Read more

Generating Trump-Style Speeches Using RNNs

Generating Trump-Style Speeches Using RNNs

Produced by Big Data Digest Compiled by: Xiao Qi, Mixed Sweet, Xia Yawei Trump’s new re-election campaign has begun. The author’s interest in Trump’s distinctive language style raises the question: can a speech that embodies his style be generated using a Recurrent Neural Network (RNN) trained on his tweets and speeches? The conclusion is that … Read more

Current Research Status of Attention Mechanisms

Current Research Status of Attention Mechanisms

Click the above“Machine Learning and Generative Adversarial Networks” to follow and star Get interesting and fun cutting-edge content! Author on Zhihu: Mr. Good Good, please delete if infringing https://zhuanlan.zhihu.com/p/361893386 1 Background Knowledge The Attention mechanism was first proposed in the field of visual images, probably in the 1990s, but it really gained popularity with the … Read more

Understanding Attention Mechanism and Its Implementation in PyTorch

Understanding Attention Mechanism and Its Implementation in PyTorch

From | Zhihu Author | Lucas Address | https://zhuanlan.zhihu.com/p/88376673 Column | Deep Learning and Emotion Computing Editor | Machine Learning Algorithms and Natural Language Processing Understanding Attention: Attention Mechanism and Its PyTorch Implementation Bionic Brain Attention Model -> Resource Allocation The deep learning attention mechanism is a bionic representation of the human visual attention mechanism, … Read more

A Simple Overview of Attention Mechanism

A Simple Overview of Attention Mechanism

Click the “AI Park” above, follow the public account, and choose to add “Star” or “Top”. Author: Synced Compiled by: ronghuaiyang Introduction The attention mechanism is neither mysterious nor complex. It is simply an interface composed of parameters and mathematics. You can insert it anywhere appropriate, and it may enhance the results. What is Attention? … Read more

Comprehensive Understanding of Attention Mechanism

Comprehensive Understanding of Attention Mechanism

Click the “AI Meets Machine Learning” above to select the “star” public account Original content delivered first-hand 1. What is Attention Mechanism? In the past two years, attention models (Attention Models) have been widely used in various types of deep learning tasks such as natural language processing, image recognition, and speech recognition, making it one … Read more

CNN Replaces RNN? When Sequence Modeling No Longer Needs Recurrent Networks

CNN Replaces RNN? When Sequence Modeling No Longer Needs Recurrent Networks

Selected from offconvex Author:John Miller Translated by Machine Heart Contributors: Qianshu, Zhang Qian, Siyuan In recent years, while Recurrent Neural Networks (RNNs) have been dominant, models like autoregressive Wavenet or Transformers are now replacing RNNs in various sequence modeling tasks. Machine Heart has previously introduced RNNs and CNNs for sequence modeling in a GitHub project, … Read more

Introducing Attention Mechanism in RNNs for Sequence Prediction

Introducing Attention Mechanism in RNNs for Sequence Prediction

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