Social Data Analytics in the Cloud with AI

1. Auflage 2024
ISBN: 978-1-032-56905-5
Verlag: CRC Press

Buch, Englisch, 184 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 435 g

The rise of cloud computing and Generative artificial intelligence (AI) has revolutionized data analytics pipelines. Analysts can collect, store, and process vast datasets in the cloud with high availability and scalability, and also leverage Generative AI to query and visualize datasets in natural languages. This pioneering textbook provides a gateway for students, educators, and professionals to develop and enhance social data analytics capabilities with the latest cloud computing and AI technologies. The textbook introduces educational cloud resources from leading technology companies, begins with foundational concepts, and progresses to advanced techniques.

Features

- The first textbook on cloud-based social data analytics with the assistance of Generative AI.

- Introduces educational cloud resources from leading technology companies like AWS, GitHub, and MongoDB.

- Presents a fully AI-powered data analytics pipeline from Python coding to data collection with APIs, cloud-based data storage, natural language queries, and interactive visualization.

- Analyzes Census and social media data with the latest large language models (LLMs).

- Provides hands-on exercises with real-world datasets on timely issues.

This textbook is an excellent resource for upper-level undergraduate and graduate students taking GIS, Urban Informatics, Social Science Data Analysis, and Data Science courses; faculty members teaching such courses; and professionals and researchers interested in leveraging cloud computing and Generative AI in social data analytics.

Zielgruppe

Academic, Professional, and Undergraduate Advanced

Autoren/Hrsg.

Wei, Xuebin

Ye, Xinyue

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Geowissenschaften Umweltwissenschaften Umwelttechnik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik
• Geowissenschaften Geologie GIS, Geoinformatik
• Interdisziplinäres Wissenschaften Wissenschaften Interdisziplinär Wirtschafts- und Sozialwissenschaften

Inhaltsverzeichnis

Introduction.  Set up a Free Cloud-based Learning Environment.  Introduction to Python Programming and Data Analytics.  Data Collection and Storage. Data Process and Query.  Data Visualization.  Conclusion.

Über Autor(innen)

Dr Xuebin Wei is an associate professor at James Madison University (JMU) and an AWS Academy Certified Educator. He earned a Ph.D. in Geography from the University of Georgia in 2015. Dr Wei has developed a series of cloud-based technology courses that promote an engaged and inclusive learning environment and helps current students prepare for future careers. He was selected as a Faculty Ambassador of the AWS Educate Cloud Ambassador Program and received the JMU Excellence in Teaching & Learning with Technology Award in 2019.

Dr Xinyue Ye is the Harold L. Adams Endowed Professor in the Department of Landscape Architecture & Urban Planning, Department of Geography, and Department of Computer Science & Engineering at Texas A&M University–College Station, where he directs the Center for Geospatial Sciences, Applications, and Technology. Dr Ye received his Ph.D. in Geography from the University of California–Santa Barbara and San Diego State University in 2010. He is a Fellow of the American Association of Geographers and a Fellow of the Royal Geographical Society.