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Elsevier Handbook of HydroInformatics Volume II - Machine Learning

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Description

Expand your technical knowledge with the Handbook of HydroInformatics: Volume II: Advanced Machine Learning Techniques. Published by Elsevier, this specialized volume provides a deep look into both the art of designing effective learning algorithms and the science behind analyzing their computational and statistical properties. This text is designed for researchers and professionals seeking to understand performance guarantees and the mathematical foundations of modern data science. Global contributors provide expert insights into theoretical topics, including minimax estimation, concentration of measure, and computational and statistical convergence rates. By exploring advanced methods such as Bayesian estimation, nonparametric regression, and nonparametric density estimation, readers gain a comprehensive understanding of how machine learning integrates with hydroinformatics. This volume serves as a vital resource for those studying the intersection of complex data analysis and environmental sciences.

Key Features

Covers the art of designing effective learning algorithms and the science of analyzing their statistical properties.

Provides theoretical foundations including computational and statistical convergence rates.

Explores advanced machine learning methods like nonparametric density estimation and nonparametric regression.

Includes expert content on minimax estimation and concentration of measure from global contributors.

Delivers technical depth on Bayesian estimation and performance guarantees for complex algorithms.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
09 December 2022
Listed Since
18 December 2019

Barcode

No barcode data available

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