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Book synopsis

Most tasks require a person or an automated system to reason - to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.

Book details

Book category Books in English Computing & information technology Computer science Artificial intelligence

• Full title: Probabilistic Graphical Models
• Author: Koller
• Language: English
• Binding: Hardback
• Number of pages: 1270
• EAN: 9780262013192
• ISBN: 0262013193
• ID: 04044192
• Publisher: MIT Press Ltd
• Weight: 2238 g
• Dimensions: 235 × 209 × 48 mm
• Date of publishing: 31. July 2009

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