Ranjitha m (3 Ergebnisse)

- Softcover
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes KönigreichGreatBookPricesUK
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Gebraucht - Wie neu
EUR 32,11
EUR 17,95 VersandVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Zustand: As New. Unread book in perfect condition.

- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 49,24
EUR 35,00 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Taschenbuch. Zustand: Neu. Neuware - 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.…

- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 58,56
EUR 43,79 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Buch. Zustand: Neu. Neuware - 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.…