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Overview: This book explores the growing focus on Artificial Intelligence (AI) systems in both industry and academia. Explainable Artificial Intelligence (XAI) comprises a set of frameworks and tools to assist us in forecasting futuristic events with the aid of Machine Learning/evolutionary and intelligent techniques. XAI helps to improve the performance of the automated models and to train the automated tools for diverse engineering purposes. XAI can also assist in the generation of feature attributions for forecasting the model behavior with respect to different inputs. XAI is used in diverse fields such as marketing, Data Science, engineering, medical science, and economics. Explainable Artificial Intelligence: A Practical Guide is a comprehensive guide to the reader which covers the fundamentals of traditional AI to the current status of XAI. In a nutshell, this book puts forward the best research roadmaps, strategies and challenges to design and develop XAI applications. The book will motivate readers to use this technology for better analysis of the needs of layman and educated users to design various use cases in XAI. The book is useful for undergraduates, postgraduates, industry, researchers and research scholars in ICT, AI, Machine Learning.
Genre: Non-Fiction > Tech & Devices
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