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Bias and Beyond is anchored in a commitment to Diversity, Equity, and Inclusion (DEI), not only as aspirational values but as methodological imperatives that must inform every aspect of data practice.
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An accessible introductory to advanced text focusing on integrating scientific computing methods and algorithms with modern data analysis techniques, including basic applications of machine learning in the sciences and engineering.
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This Element introduces computability theory and its use in explaining empirical phenomena. Aimed at advanced undergraduates and graduates in philosophy, it... Læs mere
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This book presents a semantic-based explainable framework based on knowledge graph and semantic web technology focusing on designing XAI system that... Læs mere
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This textbook for upper-year undergraduates and graduates concentrates on mining networks, a subfield within data science. Changes and updates to this edition include: new... Læs mere
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The book reviews the development process of blockchain algorithms and examples of their applications in different sectors. The opportunities and challenges of blockchain implementations that arise in making technological innovations usable in corporate structures are discussed.
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This book covers the need for IoT technologies and AI-aided IoT solutions for business and production. It shows how IoT-based... Læs mere
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This book provides examination of applications of soft computing techniques related to healthcare systems and can be used as a reference guide... Læs mere
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The book provides the reader with a broad overview of all relevant aspects involved with the responsible development, deployment and use of AI in military systems. It stresses both the advantages of AI as well as the potential downsides of including AI in military systems.
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This book is a comprehensive guide that explores the revolutionary impact... Læs mere
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This book is a comprehensive guide that explores the revolutionary impact of deep learning... Læs mere