£139.99

Springer - Recent Trends in Modelling Continuous Time Series

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Description

Explore the latest developments in data science with Recent Trends in Modelling the Continuous Time Series using Deep Learning. Published by Springer, this book provides a focused look at modern methodologies within the field of Artificial Intelligence and Machine Learning. Designed for those studying or working in Computer Science, this text addresses the complexities of continuous time series data. It serves as a resource for understanding how deep learning techniques are applied to model temporal data patterns. Whether you are a researcher or a student, this publication offers insights into the current landscape of time series analysis. This book fits into the essential academic collection for anyone interested in the intersection of deep learning and time series forecasting. By focusing on recent trends, it helps readers stay current with the evolving technological standards in the computing and internet sector.

Key Features

Published by Springer, a leading name in academic and scientific literature.

Focuses on recent trends in deep learning for continuous time series modelling.

Targeted content for professionals and students in AI and Machine Learning.

Provides technical insights into the field of Computer Science and computing.

A specialized resource for studying advanced time series data patterns.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
05 June 2026
Listed Since
06 January 2026

Barcode

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