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Overview of Intelligent Systems for Engineers and Scientists:A Practical Guide to Artificial Intelligence Book
| Title | Intelligent Systems for Engineers and Scientists:A Practical Guide to Artificial Intelligence |
| Author | Adrian A. Hopgood |
| ISBN-13 | 9781041061700 |
| Publication | CRC TBH |
The fourth edition of this bestselling textbook explains the principles of artificial intelligence (AI) and its practical applications. Using clear and concise language, it provides a solid grounding across the full spectrum of AI techniques, so that its readers can implement systems in their own domain of interest. The coverage includes knowledge-based intelligence, computational intelligence (including machine learning), and practical systems that use a combination of techniques. All the key techniques of AI are explained?including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), agents, objects, frames, symbolic learning, case-based reasoning, genetic algorithms and other optimization techniques, shallow and deep neural networks, hybrids, and the Lisp, Prolog, and Python programming languages. The book also describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control.
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Overview of Intelligent Systems for Engineers and Scientists:A Practical Guide to Artificial Intelligence Book
The fourth edition of this bestselling textbook explains the principles of artificial intelligence (AI) and its practical applications. Using clear and concise language, it provides a solid grounding across the full spectrum of AI techniques, so that its readers can implement systems in their own domain of interest. The coverage includes knowledge-based intelligence, computational intelligence (including machine learning), and practical systems that use a combination of techniques. All the key techniques of AI are explained?including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), agents, objects, frames, symbolic learning, case-based reasoning, genetic algorithms and other optimization techniques, shallow and deep neural networks, hybrids, and the Lisp, Prolog, and Python programming languages. The book also describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control.
Book Type :
Computer Science
Book Binding :
Not Available
Language :
English
No. of Pages :
514 Pages
ISBN - 10 :
1041061706
ISBN - 13 :
9781041061700
Intelligent Systems for Engineers and Scientists:A Practical Guide to Artificial Intelligence Published On :
9 January 2025
Publisher :
Taylor & Francis
Edition :
Not Available
About Adrian A. Hopgood:
Adrian A. Hopgood is the author of Intelligent Systems for Engineers and Scientists:A Practical Guide to Artificial Intelligence.
Disclaimer:
- Intelligent Systems for Engineers and Scientists:A Practical Guide to Artificial Intelligence book is not for reading online or for free download in PDF or eBook format.
- Table of Contents, Index, Syllabus, summary and image of Intelligent Systems for Engineers and Scientists:A Practical Guide to Artificial Intelligence may be of a different edition or of the same title.
- Price can change due to reprinting, price change by publisher or sourcing cost change for imported books.
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Overview of Intelligent Systems for Engineers and Scientists:A Practical Guide to Artificial Intelligence Book
| Title | Intelligent Systems for Engineers and Scientists:A Practical Guide to Artificial Intelligence |
| Author | Adrian A. Hopgood |
| ISBN-13 | 9781041061700 |
| Publication | CRC TBH |
The fourth edition of this bestselling textbook explains the principles of artificial intelligence (AI) and its practical applications. Using clear and concise language, it provides a solid grounding across the full spectrum of AI techniques, so that its readers can implement systems in their own domain of interest. The coverage includes knowledge-based intelligence, computational intelligence (including machine learning), and practical systems that use a combination of techniques. All the key techniques of AI are explained?including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), agents, objects, frames, symbolic learning, case-based reasoning, genetic algorithms and other optimization techniques, shallow and deep neural networks, hybrids, and the Lisp, Prolog, and Python programming languages. The book also describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control.