Paper Title Process Production Quality Prediction Algorithm Based on Mar-G LSTM Authors Yin Yanchao, Su Yifan (Corresponding Author), Tang Jun, Lin Wenqiang, Pu Haoran, Wang Linyu Affiliations 1. School of Mechanical and Electrical Engineering, Kunming University of Science and Technology 2. Yunnan Tobacco Industrial Co., Ltd. Funding National Key R&D Program of China (2023YFB3308401) National … Read more
Follow the public account “ML_NLP“ Set as “Starred“, heavy content delivered first time! From | Zhihu Address | https://www.zhihu.com/question/278825804/answer/402634502 Author | Tian Yu Su 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 background for deletion. I have … Read more
Click on the above “Beginner’s Guide to Visual Learning” to choose to add “Star” or “Top” Heavyweight content delivered at the first time Editor | Anke Produced by | Panchuang AI Technology Team Table of Contents: Introduction to Gated Recurrent Neural Networks Long Short-Term Memory Networks (LSTM) Gated Recurrent Units (GRU) Implementing LSTM and GRU … Read more
Originally from Python AI Frontiers This article systematically and comprehensively organizes the introduction and algorithm principles of various deep learning models. 1 Main Text Deep learning methods utilize neural network models for advanced pattern recognition and automatic feature extraction, achieving significant results in the field of data mining in recent years. Common models include not … Read more
Follow our WeChat public account “ML_NLP“ Set as “Starred“, heavy content delivered to you first! Author | Yu Wenyu Source | See the end of the article for “Read the original text” Organizer | NewBeeNLP WeChat public account BERT is great, but don’t forget our old friend RNN! Introduction CNN (Convolutional Neural Network) and RNN … Read more
1. Introduction to RNN Recurrent Neural Network (RNN) is a type of neural network used for processing sequential data. Unlike traditional feedforward neural networks, RNN introduces an “internal state” (also known as “hidden state”), which allows the network to store past information and use it to influence subsequent outputs. The updating process of this internal … Read more
Introduction to Recurrent Neural Networks Why RNN After BP Algorithm and CNN? Upon reflection on the BP algorithm and CNN (Convolutional Neural Networks), we find that their outputs only consider the influence of the previous input without taking into account the influence of inputs at other times. For instance, recognizing single objects like cats, dogs, … Read more
Original Content, First Release, No Reprints In the previous articles “Understanding Neural Networks: CNN” and “Building CNN Networks with Fashion-MNIST Dataset (Including Code)”, we provided a detailed introduction to the architecture and specific implementation of CNN networks, among which the most classic CNN networks include LeNet-5, AlexNet, GoogLeNet, ResNet, etc. Today, I will explain another … Read more
This article is a translated version of the notes from Stanford University’s CS224d course, authorized by Professor Richard Socher of Stanford University. Unauthorized reproduction is prohibited; for specific reproduction requirements, please see the end of the article. Translation: Hu Yang & Xu Ke Proofreading: Han Xiaoyang & Long Xincheng Editor’s Note: This article is the … Read more
Source: Panchuang AI, Author: VK Panchuang AI Share Author | Renu Khandelwal Compiler | VK Source | Medium We start with the following questions: Recurrent Neural Networks can solve the problems present in Artificial Neural Networks and Convolutional Neural Networks. Where can RNNs be used? What is RNN and how does it work? Challenges of … Read more