Overview
- Presents a full reference to artificial intelligence and machine learning techniques - in theory and application
- Provides a guide to AI and ML with minimal use of mathematics to make the topics more intuitive and accessible
- Connects all ML and AI techniques to applications and introduces implementations
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Table of contents (25 chapters)
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Front Matter
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Part III
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Front Matter
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Keywords
About this book
This book provides comprehensive coverage of combined Artificial Intelligence (AI) and Machine Learning (ML) theory and applications. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both perspectives to give holistic understanding. The first part introduces the concepts of AI and ML and their origin and current state. The second and third parts delve into conceptual and theoretic aspects of static and dynamic ML techniques. The forth part describes the practical applications where presented techniques can be applied. The fifth part introduces the user to some of the implementation strategies for solving real life ML problems.
The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals. It makes minimal use of mathematics to make the topics more intuitive and accessible.
- Presents a full reference to artificial intelligence and machine learning techniques - in theory and application;
- Provides a guide to AI and ML with minimal use of mathematics to make the topics more intuitive and accessible;
- Connects all ML and AI techniques to applications and introduces implementations.
Reviews
“With a good balance of theory and practice, the book effectively combines machine learning (ML) and artificial intelligence (AI) topics. Unlike other books on AI, Machine Learning and Artificial Intelligence is not very mathematically intensive, which makes it easier to read. Overall, its language is very easy to follow. Each chapter has introduction and conclusion sections, and many helpful figures explain the concepts.” (Computing Reviews)
“This book provides a thorough description of mathematical tools needed to learn and practice Machine Learning for many real time applications ...” (Sitharama Iyengar, University Distinguished Professor, Florida International University, Miami, Florida)Authors and Affiliations
About the author
Bibliographic Information
Book Title: Machine Learning and Artificial Intelligence
Authors: Ameet V Joshi
DOI: https://doi.org/10.1007/978-3-030-26622-6
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Softcover ISBN: 978-3-030-26624-0Published: 07 October 2020
eBook ISBN: 978-3-030-26622-6Published: 24 September 2019
Edition Number: 1
Number of Pages: XXII, 261
Number of Illustrations: 4 b/w illustrations, 94 illustrations in colour
Topics: Communications Engineering, Networks, Machine Learning, Computational Intelligence, Data Mining and Knowledge Discovery, Information Storage and Retrieval, Big Data/Analytics