Click on the top "Xiaobai Learns Vision", select to add "Star" or "Pin" Heavyweight content delivered at the first time Introduction RNN (Recurrent Neural Network) is an artificial neural network with nodes oriented in a circular connection. Unlike feedforward neural networks, RNNs can utilize internal memory to process any sequential input series, meaning they learn … Read more
Source: Algorithm Advancement This article is approximately 11,000 words long and is recommended for a reading time of over 20 minutes. For complex nonlinear patterns, deep learning models have strong expressive capabilities. 1 Overview Deep learning methods are a type of machine learning that utilizes neural network models for advanced pattern recognition and automatic feature … Read more
XU Wanxu, SHEN Yindong (School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, Hubei 430074) Abstract: Traditional bus travel time prediction models often ignore information from historical timestamps, leading to unsatisfactory prediction accuracy. To address the temporal nature of bus travel times, this paper proposes a prediction model based on the … 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 on the “Datawhalee” above to select the “Starred“ public account Get valuable content at the first time Training techniques are very important for deep learning. As a highly experimental science, using different training methods on the same network structure can yield significantly different results. Here, I summarize my experiences from the past year and … Read more
Hello, I am Xiao Chu~ Today we are going to talk about a topic: using LSTM and KNN for multivariate data anomaly detection. Related Principles Multivariate Data Anomaly Detection is a very important task, especially in complex contexts such as high-dimensional data and time series data. Traditional anomaly detection methods (such as those based on … Read more
Big Data Digest Work Students studying the Stanford CS231n open course, take note! The detailed explanations for Assignment 1 – 3 are now available! Yesterday, Big Data Digest initiated a call for participants in the course by Andrew Ng and Li Fei-Fei, and the enthusiasm for the#SpringFestivalCheckIn# activity was exceptionally high! The Digest team has … Read more
In this blog, we will delve into the fascinating world of action recognition using the UCF101 dataset. Action recognition is a key task in computer vision, with applications ranging from surveillance to human-computer interaction. The UCF101 dataset serves as our playground for this exploration. Our goal is to build an action recognition model that combines … 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
Author: Occam’s Razor Personal Blog: https://blog.csdn.net/yilulvxing Paper Link: https://arxiv.org/abs/1704.02971 Github Code Link: https://github.com/LeronQ/DA-RNN The paper is titled “Recurrent Neural Network Based on Two-Stage Attention Mechanism”. Essentially, the article is based on the Seq2Seq model, combined with an attention mechanism to realize time series prediction methods. A major highlight of the article is that it introduces … Read more