Time series data

Understanding Multivariate Probabilistic Time Series Forecasting with Informer

Time series forecasting has long been regarded as a critical component in myriad fields, ranging from finance and economics to environmental science and engineering. Accurate predictions of future observations enable businesses, researchers, and policymakers to make informed decisions, optimize resource allocation, and mitigate potential risks. However, real-world time series data often exhibit complex patterns and …

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Transform Your Recommender System with Temporal Graph Neural Networks

Introduction Recommender systems have revolutionized the way we discover new products, music, movies, and even potential romantic partners. They analyze users’ past interactions with items and provide personalized recommendations based on their preferences. However, traditional recommender systems face several challenges, such as sparsity, cold-start, and scalability. To overcome these limitations, researchers have been exploring the …

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Optimizing the Accuracy of Time Series Predictions: An Introduction to the Forward-Backward Algorithm

Introduction In today’s fast-paced world, businesses, industries, and organizations rely heavily on data-driven decision making. The ability to predict future trends and patterns in data can be incredibly valuable for forecasting and planning. One of the most important areas of data analysis is time series analysis, which involves studying and understanding sequential data over time. …

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