This book presents a summary of artificial intelligence and machine learning techniques in its first two chapters. The remaining chapters of the book provide everything one must know about the basic artificial intelligence to modern machine intelligence techniques including the hybrid computational intelligence technique, using the concepts of several real-life solved examples, design of projects and research ideas. The solved examples with more than 200 illustrations presented in the book are a great help to instructors, students, non–AI professionals, and researchers. Each example is discussed in detail with encoding, normalization, architecture, detailed design, process flow, and sample input/output. Summary of the fundamental concepts with solved examples is a unique combination and highlight of this book.
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Dr. Priti Srinivas Sajja has been working at the Post Graduate Department of Computer Science, Sardar Patel University, India, since 1994, and presently holds the post of Professor. She specializes in Artificial Intelligence and Machine Learning and has produced over 210 publications, which include seven books, two edited books, and thirteen book chapters. She is the author of Essence of Systems Analysis and Design (Springer, 2017) and co-author of Intelligent Techniques for Data Science (Springer, 2016), Intelligent Technologies for Web Applications (CRC Press, 2012), and Knowledge-Based Systems (J&B, 2009) published in Singapore, Switzerland, and the USA, and three books published in India. Further, she did major research projects funded by the University Grants Commission, India and Department of Science and Technology, India.
This book presents a summary of artificial intelligence and machine learning techniques in its first two chapters. The remaining chapters of the book provide everything one must know about the basic artificial intelligence to modern machine intelligence techniques including the hybrid computational intelligence technique, using the concepts of several real-life solved examples, design of projects and research ideas. The solved examples with more than 200 illustrations presented in the book are a great help to instructors, students, non–AI professionals, and researchers. Each example is discussed in detail with encoding, normalization, architecture, detailed design, process flow, and sample input/output. Summary of the fundamental concepts with solved examples is a unique combination and highlight of this book.
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