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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Ethics in Data Science is a practical guide to navigatie the moral challenges of modern data use, covering topics from ethical data collection and privacy to algorithmic bias and AI accountability. The book offers clear frameworks, real-world case studies, and regulatory insights. Each chapter includes learning outcomes, summaries, and assessments to reinforce the understanding of the readers. The book is designed for students, educators, and professionals. This book emphasizes transparency, fairness, and responsibility in every stage of the data lifecycle - whether it is with regard to building models or shaping policies - and helps to make ethical decisions in an increasingly data-driven world.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Ethics in Data Science is a practical guide to navigatie the moral challenges of modern data use, covering topics from ethical data collection and privacy to algorithmic bias and AI accountability. The book offers clear frameworks, real-world case studies, and regulatory insights. Each chapter includes learning outcomes, summaries, and assessments to reinforce the understanding of the readers. The book is designed for students, educators, and professionals. This book emphasizes transparency, fairness, and responsibility in every stage of the data lifecycle - whether it is with regard to building models or shaping policies - and helps to make ethical decisions in an increasingly data-driven world.