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AI-Driven Time Series Forecasting: Complexity-Conscious Prediction and Decision-Making

AI-Driven Time Series Forecasting: Complexity-Conscious Prediction and Decision-Making

AI-Driven Time Series Forecasting: Complexity-Conscious Prediction and Decision-Making Paperback - 2023

by Raghurami Reddy Etukuru Ph.D

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Paperback. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; When you enter the world of time series analysis, you step into a labyrinth of numerical patterns, where each turn you take unveils another layer of complexity. Here, simple mathematical or statistical models struggle to keep pace. Real
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Details

  • Title AI-Driven Time Series Forecasting: Complexity-Conscious Prediction and Decision-Making
  • Author Raghurami Reddy Etukuru Ph.D
  • Binding Paperback
  • Condition New
  • Pages 254
  • Volumes 1
  • Language ENG
  • Publisher iUniverse
  • Publication date 2023-10-06
  • Bookseller's Inventory # ria9781663256713_inp
  • ISBN 9781663256713 / 1663256713
  • Weight 1.76 lbs (0.80 kg)
  • Dimensions 11 x 8.5 x 0.69 in (27.94 x 21.59 x 1.75 cm)
  • Category Computers - General Information
  • Quantity available 766

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Reader reviews for AI-Driven Time Series Forecasting: Complexity-Conscious Prediction and Decision-Making

From the publisher

When you enter the world of time series analysis, you step into a labyrinth of numerical patterns, where each turn you take unveils another layer of complexity. Here, simple mathematical or statistical models struggle to keep pace. Reality is riddled with complex patterns in time series data, which, like cryptic pieces of a jigsaw puzzle, hold the key to unraveling insightful predictions. These complex patterns include non-linearity, non-stationarity, long memory or dependence, asymmetry, and stochasticity. But what creates these intricate patterns? Raghurami Reddy Etukuru, Ph.D., a distinguished and adaptable specialist in data science and artificial intelligence, delves into that question in this groundbreaking book, explaining that the factors are numerous and multifaceted, each adding their own measure of challenge. He doesn't just discuss problems but also addresses the forecasting of time series amidst intricate patterns. Take a deep dive deep into the world of numbers and patterns, so you can unravel complexities and leverage the power of artificial intelligence to enhance predictive capabilities. More than just a theoretical guide, this book is a practical companion in the often-turbulent journey of understanding and predicting complex time series data.
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