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Springer - Intelligent Data Analysis: An Introduction

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Description

Master the fundamentals of data science with Intelligent Data Analysis: An Introduction by Springer. This monograph serves as a comprehensive guide to the most important methods used in modern data analysis. Through twelve well-structured chapters, leading experts provide a deep look into the core issues facing the field today. The text is organized to build your knowledge systematically. The first half focuses on classical statistical foundations, covering essential topics from basic probability and general inference to advanced multivariate and time series methods. You will also find detailed discussions on Bayesian approaches and Support Vector Machines. Designed for students and professionals in computer science and machine learning, this book bridges the gap between traditional statistics and modern computational techniques. It offers a clear path for anyone looking to understand how intelligent methods can be applied to complex data sets.

Key Features

Comprehensive coverage of key intelligent data analysis methods through twelve coherent chapters written by leading experts.

Strong foundation in classical statistical issues including probability, inference, and multivariate methods.

In-depth exploration of advanced topics such as time series methods and Bayesian approaches.

Detailed technical discussion on Support Vector Machines and their role in data analysis.

Structured learning path that transitions from basic statistical concepts to complex machine learning applications.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
19 March 2003
Listed Since
15 February 2007

Barcode

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