£104.72

Springer Analytics Modeling in Reliability and Machine Learning

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£113.76 £103.82 £105.99 £108.16 £110.32 £112.49 £114.66 13 March 2026 22 March 2026 31 March 2026 09 April 2026 18 April 2026

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Description

Explore the intersection of reliability engineering and modern data science with this comprehensive text from the Springer Series in Reliability Engineering. As billions of people connect via mobile devices, the volume of data collected has reached unprecedented levels. This book addresses the challenges of this big data era by presenting novel research and application chapters focused on statistics and machine learning. Readers will find a deep dive into analytical models and computational techniques. The content covers essential topics including AI, optimization, and statistical inference. Whether you are working in manufacturing, health care, or general industry, these chapters provide the technical foundation needed to apply machine learning algorithms to complex reliability problems. This resource is designed for those looking to navigate the modern landscape of data science and reliability through advanced computational methods.

Key Features

Covers novel research in reliability, statistics, and machine learning to help you stay current with industry advancements.

Focuses on analytical models and techniques designed for practical use in reliability engineering and data science.

Provides insights into applying AI and optimization methods across various sectors including manufacturing and health care.

Addresses big data challenges through the study of machine learning algorithms and statistical inference.

Part of the respected Springer Series in Reliability Engineering, ensuring high-quality academic and professional content.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
21 January 2025
Listed Since
13 August 2024

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