Machine Learning and Artificial Intelligence - Erstausgabe

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ISBN/EAN: 9783030266226

ISBN - alternative Schreibweisen:
978-3-030-26622-6

Daten vom Verlag:

Autor/in: Ameet V Joshi
Titel: Machine Learning and Artificial Intelligence
Verlag: Springer; Springer International Publishing
261 Seiten
Erscheinungsjahr: 2019-09-24
Cham; CH
Gedruckt / Hergestellt in Großbritannien.
Sprache: Englisch
74,89 € (DE)
77,00 € (AT)
82,50 CHF (CH)
Available
XXII, 261 p. 98 illus., 94 illus. in color.

EA; E107; eBook; Nonbooks, PBS / Technik/Elektronik, Elektrotechnik, Nachrichtentechnik; Nachrichtententechnik, Telekommunikation; Verstehen; Artificial Intelligence; ML Techniques; Modern perspective on AI and ML; AI reference; ML reference; AI and Machine Learning; B; Communications Engineering, Networks; Machine Learning; Computational Intelligence; Data Mining and Knowledge Discovery; Information Storage and Retrieval; Big Data/Analytics; Communications Engineering, Networks; Machine Learning; Computational Intelligence; Data Mining and Knowledge Discovery; Information Storage and Retrieval; Data Analysis and Big Data; Engineering; Maschinelles Lernen; Künstliche Intelligenz; Data Mining; Wissensbasierte Systeme, Expertensysteme; Informationsrückgewinnung, Information Retrieval; Data Warehousing; Datenbanken; BB

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