Friends familiar with deep learning know that LSTM is a type of RNN model that can conveniently handle time series data and is widely used in fields such as NLP. After watching Professor Li Hongyi’s deep learning videos from National Taiwan University, especially the first part introducing RNN and LSTM, I felt enlightened. This article … 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
Source: Machine Learning Algorithms Explained Friends familiar with deep learning know that LSTM is a type of RNN model that can conveniently handle time series data and is widely used in fields such as NLP. After watching Professor Li Hongyi’s deep learning videos from National Taiwan University, especially the first part introducing RNN and LSTM, … 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
1 Algorithm History In 1986, Elman and others proposed the Recurrent Neural Network for processing sequential data. Just as Convolutional Neural Networks are specifically designed for processing two-dimensional data (such as images), Recurrent Neural Networks are specialized for handling sequential information. Recurrent networks can be extended to longer sequences, and most recurrent neural networks can … 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
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
Hello everyone, I am Peter~ Today I am sharing an article about deep learning algorithms, mainly introducing 10 deep learning algorithms such as CNN, LSTM, RNN, GAN, MLP, etc. Introduction Deep learning is a subset of machine learning, based on artificial neural networks. The learning process is considered deep because the structure of artificial neural … Read more
Source: Artificial Intelligence AI Technology This article is about 6000 words long and is recommended to read in 12 minutes. This article introduces your understanding of CNN and RNN. This article mainly focuses on understanding CNN and RNN, summarizing their advantages through comparison while deepening one’s understanding of this area of knowledge. The code references … 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