Machine Learning and Artificial Intelligence
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Beschreibung
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.
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.
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
Autor*in
Ameet V Joshi
Themen in »Machine Learning and Artificial Intelligence«
Artificial Intelligence ML Techniques Modern perspective on AI and ML AI reference ML reference AI and Machine Learning
Stimmen zu »Machine Learning and Artificial Intelligence«
“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)()