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The new edition of this popular professional book on artificial
intelligence (ML) and machine learning (ML) has been revised for
classroom or training use. The new edition provides comprehensive
coverage of combined AI and 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 fourth 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. Each chapter is accompanied with a
set of exercises that will help the reader / student to apply the
learnings from the chapter to a real-life problem. Completion of
these exercises will help the reader / student to solidify the
concepts learned. 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. The book covers a large gamut
of topics in the area of AI and ML and a professor can tailor a
course on AI / ML based on the book by selecting and re-organizing
the sequence of chapters to suit the needs.
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.
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