9780367571641-0367571641-Artificial Intelligence (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)

Artificial Intelligence (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)

ISBN-13: 9780367571641
ISBN-10: 0367571641
Edition: 2
Author: Richard E. Neapolitan
Publication date: 2020
Publisher: Routledge
Format: Paperback 480 pages
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Book details

ISBN-13: 9780367571641
ISBN-10: 0367571641
Edition: 2
Author: Richard E. Neapolitan
Publication date: 2020
Publisher: Routledge
Format: Paperback 480 pages

Summary

Artificial Intelligence (Chapman & Hall/CRC Artificial Intelligence and Robotics Series) (ISBN-13: 9780367571641 and ISBN-10: 0367571641), written by authors Richard E. Neapolitan, was published by Routledge in 2020. With an overall rating of 4.3 stars, it's a notable title among other AI & Machine Learning (Systems Analysis & Design, Computer Science, Game Programming, Programming, Software Design, Testing & Engineering) books. You can easily purchase or rent Artificial Intelligence (Chapman & Hall/CRC Artificial Intelligence and Robotics Series) (Paperback) from BooksRun, along with many other new and used AI & Machine Learning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $1.52.

Description

The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods.
The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding.
Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more.

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