Forecasting
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N-BEATS — The First Interpretable Deep Learning Model That Worked for Time Series Forecasting | by Jonte Dancker | May, 2024
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An easy-to-understand deep dive into how N-BEATS works and how you can use it.11 min read·23 hours agoArchitecture of N-BEATS (Image taken from Oreshkin et ...

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Beyond the Analyst: AI-Powered Equities Research Forecasting – AI Time Journal
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Images courtesy of Dalle-2 Equities Research: A Cornerstone of Investment Decisions Equities research is a fundamental pillar of the investment process. It ...

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Advancing Time Series Forecasting: The Impact of Bi-Mamba4TS’s Bidirectional State Space Modeling on Long-Term Predictive Accuracy
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Time series forecasting is increasingly vital across numerous sectors, such as meteorology, finance, and energy management. Its relevance has grown as ...

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Demand Forecasting Excellence: Best Practices in Demand Management
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In the dynamic landscape of modern business, demand forecasting stands as a cornerstone of effective demand management. By accurately predicting future ...

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Convolutional LSTM for spatial forecasting
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This post is the first in a loose series exploring forecasting of spatially-determined data over time. By spatially-determined I mean that whatever the ...

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Budgeting, Forecasting, And Goal-Setting In Your Construction Company
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The M.A.P. Way Budgets are invaluable business tools because they help you manage your finances effectively. A budget is a plan for how you will spend ...

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Forecasting El Niño-Southern Oscillation (ENSO)
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Today, we use the convLSTM introduced in a previous post to predict El Niño-Southern Oscillation (ENSO). ENSO refers to a changing pattern of sea surface ...

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iTransformer: The Latest Breakthrough in Time Series Forecasting | by Marco Peixeiro | Apr, 2024
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Discover the architecture of iTransformer and apply the model in a small experiment using Python.Photo by David Clode on UnsplashThe field of forecasting ...

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Introductory time-series forecasting with torch
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This is the first post in a series introducing time-series forecasting with torch. It does assume some prior experience with torch and/or deep learning. ...

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