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Springer Statistical Models and Learning Methods for Complex Data - Springer

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Description

Statistical Models and Learning Methods for Complex Data is a comprehensive academic text from Springer that explores advanced statistical methodologies and machine learning approaches essential for handling intricate datasets. This Studies in Classification, Data Analysis, and Knowledge Organization volume provides researchers, data scientists, and academics with in-depth coverage of statistical modelling techniques specifically designed for complex data structures. The book bridges classical statistical theory with contemporary machine learning methods, offering practical insights into classification, data analysis, and knowledge organisation. Ideal for professionals working in artificial intelligence, computer science, and data science fields, this Springer publication serves as both a reference guide and a learning resource for mastering sophisticated analytical methods required in modern data-driven environments.

Key Features

Springer publication covering statistical models and learning methods tailored for handling complex data analysis scenarios.

Part of the Studies in Classification, Data Analysis, and Knowledge Organization series offering rigorous academic content.

Focuses on machine learning and artificial intelligence methodologies within the computer science and data science domains.

Provides comprehensive coverage of statistical modelling techniques applicable to real-world complex datasets.

Designed for researchers and professionals seeking advanced knowledge in data analysis and knowledge organisation.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
02 October 2025
Listed Since
08 January 2025

Barcode

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