Data-Driven Applications for Emerging Technologies

Data-Driven Applications for Emerging Technologies explores the practical use of data science in AI, healthcare, sustainability, and security. It covers key topics like predictive modelling, deep learning, and natural language processing, offering a mix of theory and hands-on applications. The book highlights how data-driven techniques can improve decision-making, optimize processes, and solve real-world problems.
Each chapter includes research contributions from academics and industry professionals, making the content both relevant and accessible. Readers will find practical insights into applying machine learning frameworks, data preprocessing techniques, and emerging technologies across different domains.
Designed for researchers, professionals, and students, this book provides a solid foundation in data-driven methods without being overly technical. Whether you're looking to enhance your understanding of AI and machine learning or apply data science in real-world scenarios, this book serves as a useful and practical resource.

Product details

• Authors: Nazmul (University of Ulster Siddique
• Assisted by: Mohammad Shamsul Arefin (Editor), Aminul Haque (Editor), S. M. Aminul Haque (Editor), Ahmed Wasif Reza (Editor), Ahmed Wasif Reza Reza (Editor), Siddique Nazmul (Editor)
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Release: 17.10.2025, delayed
• EAN: 9781032996936
• ISBN: 978-1-0-3299693-6
• No. of pages: 266
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; Data Mining, COMPUTERS / Computer Science, Computer-Aided Design (CAD), COMPUTERS / Information Technology, computer science, COMPUTERS / Computer Engineering, Information technology: general issues, Computer networking & communications, Information technology: general topics, Database design and theory, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Database Administration & Management, Computer networking and communications, COMPUTERS / Business & Productivity Software / Databases, Database design & theory, technology;data science;applied informatics;computer science