Source: Time Series Research This article is approximately 2800 words long and is recommended for a 5-minute read. This article proposes a higher-order Transformer architecture specifically designed to handle multimodal stock data for predicting stock movements. For investors and traders, predicting stock movements in the financial market is crucial as it enables them to make … Read more
Star★TopPublic Account I love you all♥ Author: Matthew Translated by: Fang’s Mantou 0 Introduction Today, the public account will introduce to everyone,distinguishing real financial time series from synthetic time series. The data is anonymous, and we do not know which time series comes from which asset. In the end, we achieved a 67% in-sample testing … Read more
↑↑↑ Follow and Star “Datawhale” Daily insights & monthly study groups, don’t miss out Datawhale Insights Source: Jason Brownlee, Organized by Data Science THU This article is approximately 3300 words, and is recommended to read in 10minutes This article introduces how to use XGBoost for time series forecasting, including transforming time series into a supervised … Read more
Author: Mirko Translated by: Sour Bun Wishing you a peaceful Dragon Boat Festival Generative Adversarial Network Applications in Quantitative Investing Series (Part 1) Get the complete code at the end of the article 1 Introduction Overfitting is one of the challenges we face when applying machine learning techniques to time series. This issue arises because … Read more
Big Data Digest Work Compiled by: Wang Yiding, Xiu Zhu, Ruan Xuenni,Ding Hui, Qian Tianpei NVIDIA released the “world’s largest GPU” yesterday while experiencing a stock price drop of more than $20, which has not recovered by the time of this publication. Countless students are asking in the background whether they should buy the dip? … Read more
Click the blue text to follow us Happy New Year, wishing you good fortune in the Year of the Dragon Happy Spring Festival LSTM Neural Network Time Series Prediction Given a simple dataset, we use Long Short-Term Memory (LSTM) neural networks to implement time series prediction, with the ReLU function as the activation function. The … Read more
Source: Deep Learning Enthusiasts Author on Zhihu | Master Su Link | https://zhuanlan.zhihu.com/p/139617364 This article is about 3200 words, and it is recommended to read in 5 minutes This article introduces the visualization of the LSTM model structure. Recently, I have been studying the application of LSTM in time series prediction, but I encountered a … Read more
【Introduction】Time series modeling is widely used in machine translation, speech recognition, and other related fields, making it an essential technology in the AI domain. This article will teach you how to build a Long Short-Term Memory network (LSTM) from scratch, using Bitcoin price prediction as an example. Author | Brian Mwangi Translated by | Zhuanzhi … Read more
Editorial Department WeChat Official Account Keywords All Network Search Latest Ranking “Quantitative Investment”: Rank One “Quantization”: Rank One “Machine Learning”: Rank Four We will continue to strive To become a high-qualityFinancial and Technical public account Introduction to LSTM Networks LSTM Networks are a type of Recurrent Neural Network (RNN) first introduced by Sepp Hochreiter and … Read more
↑↑↑ Follow for “Star Mark“Kaggle Competition Guide Kaggle Competition Guide Author: Fareise, excerpted from Yuan Yuan’s Algorithm Notes Using RNN for Long-Term Time Series Forecasting, Is It Better Than Transformer SOTA? This article introduced today comes from South China University of Technology, proposing an RNN-based long-term time series forecasting model that outperforms the SOTA Transformer … Read more