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Introducing issues in dynamic memory and case-based reasoning, this comprehensive volume presents extended descriptions of four major programming efforts conducted at Yale during the past several years. Each descriptive chapter is followed by a companion chapter containing the m…
Learn the ins and outs of decisions, biases, and reliability of AI algorithms and how to make sense of these predictions. This book explores the so-called black-box models to boost the adaptability, interpretability, and explainability of the decisions made by AI algorithms usin…
This book proposes tools for analysis of multidimensional and metric data, by establishing a state-of-the-art of the existing solutions and developing new ones. It mainly focuses on visual exploration of these data by a human analyst, relying on a 2D or 3D scatter plot display o…
"The great majority of books on artificial intelligence are written by AI experts who understandably focus on its achievements and potential transformative effects on society. In contrast, AI vs. Humans is written by two psychologists (Michael and Christine Eysenck) whose perspe…
"The great majority of books on artificial intelligence are written by AI experts who understandably focus on its achievements and potential transformative effects on society. In contrast, AI vs. Humans is written by two psychologists (Michael and Christine Eysenck) whose perspe…
"The great majority of books on artificial intelligence are written by AI experts who understandably focus on its achievements and potential transformative effects on society. In contrast, AI vs. Humans is written by two psychologists (Michael and Christine Eysenck) whose perspe…
