Verwandte Artikel zu Statistics and Data Foundations for Ai

Statistics and Data Foundations for Ai - Hardcover

Dasu, Tamraparni; Murthy, Geetha

 
9781041006428: Statistics and Data Foundations for Ai
Hardcover
ISBN 10: 104100642X ISBN 13: 9781041006428
Verlag: CRC Press, 2026

Inhaltsangabe

Statistics and Data Foundations for AI is an interdisciplinary approach to statistical concepts and data foundations of AI with real-world illustrative examples from authoritative sources such as NASA, NOAA and the US Census Bureau. Co-authored by a data science research expert and an experienced educator, the book serves as a prequel to an AI and machine learning course.

Given the interdependence of data and AI, understanding data and using it responsibly to create and interact with AI tools requires a high level of statistical skill and data intuition. The book includes topics such as data management, exploratory data analysis, sampling, probability theory, hypothesis testing, multivariate analysis, data quality, ethics, data privacy, and responsible use of AI. Every key statistical concept is presented in the context of how it is used by AI applications in areas such as sports, fashion, climate science, environmental science, health, medicine and space exploration. The book makes AI relatable to everyday life so that it is no longer an abstraction. Instructor resources, supplementary materials, further reading and debate topics enable advanced study and deeper thinking.

Statistics and Data Foundations for AI is intended for undergraduate and graduate students, and practitioners interested in learning statistical foundations in relation to data and AI with application to real world problems. The content is accessible to learners from a wide variety of backgrounds (STEM and non-STEM) without sacrificing rigor.

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Über die Autorin bzw. den Autor

Tamraparni Dasu (Ph.D. Mathematical Statistics, University of Rochester, 1991) is a research scientist and Data Science expert specializing in computational statistics, machine learning and data quality. She retired in 2021 as Lead Inventive Scientist after 31 years at AT&T Bell Laboratories and now teaches Data Mining, Machine Learning and AI as an adjunct professor at Fairleigh Dickinson University, New Jersey. Dr. Dasu has published extensively in top tier journals and research conferences such as SIGMOD, KDD and VLDB. As an educator, Dr. Dasu is committed to mentoring the next generation of quantitative thinkers, computer scientists and data scientists.

Geetha Murthy (Ed.D. Instructional Leadership, St. John’s University, Queens, NY 2015) is a highly experienced school administrator and math teacher whose research focused on describing and dismantling self-limiting beliefs in students that inhibit students from pursuing STEM education/careers. Most recently, Dr. Murthy served as the K-12 director of mathematics for Herricks School District in Long Island, NY, a high performing public school district which made significant progress under her leadership in increasing student achievement through initiatives that focused on systemic changes to create and sustain greater equity, access and success for all students. Dr. Murthy is passionate about promoting 21st Century Skills in teaching and learning.

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Verlag
CRC Press
Erscheinungsdatum
2026
Sprache
Englisch
ISBN 10 
104100642X
ISBN 13 
9781041006428
Einband
Gebundene Ausgabe
Anzahl der Seiten
272
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
Nicht verfügbar