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Machine Learning and Artificial Intelligence
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Machine Learning and Artificial Intelligence

2020 ed.

Book Details

Format Paperback / Softback
ISBN-10 3030266249
ISBN-13 9783030266240
Edition 2020 ed.
Publisher Springer Nature Switzerland AG
Imprint Springer Nature Switzerland AG
Country of Manufacture GB
Country of Publication GB
Publication Date Oct 7th, 2020
Print length 261 Pages
Product Classification: Artificial intelligenceMachine learning
Ksh 12,600.00
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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.


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