Artificial intelligence for data science in theory and practice / Mohamed Alloghani, Christopher Thron, Saad Subair, editors.
Alloghani, Mohamed, editor.; Thron, Chris, editor.; Subair, Saad, editor.
2022
Q336 .A75 2022
Available Online

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Title Artificial intelligence for data science in theory and practice / Mohamed Alloghani, Christopher Thron, Saad Subair, editors.
ISBN 9783030922450 (electronic bk.)
3030922456 (electronic bk.)
9783030922443
3030922448
DOI https://doi.org/10.1007/978-3-030-92245-0
Published Cham : Springer, [2022]
Copyright ©2022
Language English
Description 1 online resource : illustrations (some color).
Item Number 10.1007/978-3-030-92245-0 doi
Call Number Q336 .A75 2022
Dewey Decimal Classification 006.3
Summary This book provides valuable information on effective, state-of-the-art techniques and approaches for governments, students, researchers, practitioners, entrepreneurs and teachers in the field of artificial intelligence (AI). The book explains the data and AI, types and properties of data, the relation between AI algorithms and data, what makes data AI ready, steps of data pre-processing, data quality, data storage and data platforms. Therefore, this book will be interested by AI practitioners, academics, researchers, and lecturers in computer science, artificial intelligence, machine learning and data sciences. Presents approaches to artificial intelligence taken by various sectors; Includes development-related applications in AI from around the world; Discusses AI in government, healthcare, education, tourism in addition to AI ethics. .
Note Includes index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed April 13, 2022).
Added Author Alloghani, Mohamed, editor.
Thron, Chris, editor.
Subair, Saad, editor.
Series Studies in computational intelligence ; v. 1006.
Available in Other Form Print version: 9783030922443
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
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Introduction
Part I: Government services
Intelligent chat bots for online customer service
Improved services delivery using AI
Intelligent policing: physical crime and cybercrime prevention and detection
Part II: Healthcare Services
Breast cancer diagnosis
IoT Pharmaceutical management
Biomedical Text conversion algorithms
Part III: Education
Machine learning in teaching and assessment of students
Prediction of student performance
Training the next generation of AI students
Part IV: Tourism and hospitality
Landmark recognition
Recommender system for tourists
Part V: AI Ethics
Ethics of facial recognition
Ethics of robotic services
Bias issues and misapplication of machine learning
Conclusion.

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