Priti Srinivas Sajja – författare

This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions./p>

The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for real‐world applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.

The main objective is to provide quick and essential knowledge for the subject with the help of summary and solved questions /case studies without going into detailed discussion. This book will be much helpful for the students as a supplementary text/workbook; and to the non-computer professionals, who deal with the systems analysis and design as part of their business. Such problem solving approach will be able to provide practical knowledge of the subject and similar learning output, without going into lengthy discussions.

Though the book is conceived as supplementary text/workbook; the topics are selected and arranged in such a way that it can provide complete and sufficient knowledge of the subject.

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.