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- An Introduction to Knowledge Engineering
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Artikel #:
90807070
An Introduction to Knowledge Engineering
Artikel #:
90807070
€ 58
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Naročite zdaj in dobite okoli dne: Petek, Avgust 14
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An Introduction to Knowledge Engineering presents a simple but detailed exploration of current and established work in the field of knowledge-based systems.
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What Stands Out
Foundational Concepts
Offers a clear overview of essential knowledge engineering principles, making it perfect for beginners eager to build a solid understanding and application in real-world scenarios.
Practical Applications
Includes case studies and examples that demonstrate how knowledge engineering is applied in various industries, providing readers with tangible insights and enhancing learning effectiveness.
Accessible Language
Written in a straightforward style, this introduction ensures that complex concepts are easily understood, catering to diverse audiences, including students and professionals entering the field.
Podrobnosti produkta
| Publisher | Springer |
| Publication date | October 4, 2006 |
| Edition | 2007th |
| Language | English |
| Print length | 300 pages |
| ISBN-10 | 1846284759 |
| ISBN-13 | 978-1846284755 |
| Item Weight | 15 ounces (425.25 grams) |
| Dimensions | 6.14 x 0.68 x 9.25 inches (15.6 x 1.7 x 23.5 cm) |
OPIS IZDELKA
An Introduction to Knowledge Engineering
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Vprašanje:
Who is this book suitable for?
Odgovor: The book is suitable for undergraduate and postgraduate students in computing science, knowledge engineering, AI, and related disciplines. -
Vprašanje:
What topics does the book cover?
Odgovor: It covers a variety of technologies including expert systems, neural networks, and intelligent agents among others. -
Vprašanje:
Does the book include activities for readers?
Odgovor: Yes, it includes numerous activities and self-assessment questions to enhance understanding.
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Naročite zdaj in dobite okoli dne: Petek, Avgust 14
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Značilnosti in prednosti
- Comprehensive introduction to knowledge-based systems and technologies.
- Covers expert systems, neural networks, genetic algorithms, and more.
- Includes numerous activities for reader engagement and research.
- Self-assessment questions ensure understanding of concepts.
- Ideal for undergraduate and postgraduate students in computing fields.
- Reinforces knowledge applicable to various disciplines like AI and robotics.
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