AI-Driven Time Series Forecasting

Raghurami Reddy Etukuru

ISBN 10: 1663256713 / ISBN 13: 9781663256713

Editore: iUniverse, 2023

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Dati bibliografici

• Titolo: AI-Driven Time Series Forecasting
• Editore: iUniverse
• Data di pubblicazione: 2023
• Lingua: Inglese
• ISBN 10: 1663256713
• ISBN 13: 9781663256713
• Rilegatura: Paperback
• Condizione: New
• Dimensioni: 21,59 L x 1,75 A x 27,94 P centimetri 21,59 centimetri di larghezza per 1,75 centimetri di altezza per 27,94 centimetri di profondità
• Peso: 798 grammi

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Riassunto

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.