Data Analytics using Machine Learning Techniques on Cloud Platforms

1. Auflage 2025
ISBN: 978-1-032-49146-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 204 Seiten, Format (B × H): 156 mm x 234 mm

Data Analytics using Machine Learning Techniques on Cloud Platforms examines how machine learning (ML) and cloud computing combine to drive data-driven decision-making across industries. Covering ML techniques, loud-based analytics tools and security concerns, this book provides theoretical foundations and real-world applications in fields like healthcare, logistics and e-commerce. It also addresses security challenges, privacy concerns and compliance frameworks, ensuring a comprehensive understanding of cloud-based analytics.

This book:

- Covers supervised and unsupervised learning, including regression, clustering, classification and neural networks

- Discusses Hadoop, Spark, Tableau, Power BI and Splunk for analytics and visualization

- Examines how cloud computing enhances scalability, efficiency and automation in data analytics

- Showcases ML-driven solutions in e-commerce, supply chain logistics, healthcare and education

This book is an essential resource for students, researchers and professionals who seek to understand and apply ML-driven cloud analytics in real-world scenarios.

Zielgruppe

Academic, Postgraduate, and Undergraduate Advanced

Autoren/Hrsg.

Katal, Avita

Rawat, Seema

Ahuja, Neelu Jyothi

Kumar, Praveen

Urooj, Shabana

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Spiele-Programmierung, Rendering, Animation
• Mathematik | Informatik EDV | Informatik Informatik
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Cloud-Computing, Grid-Computing
• Mathematik | Informatik EDV | Informatik Technische Informatik

Inhaltsverzeichnis

Preface

Author biography

Introduction

1. Data Analytics: An Overview 2. Data Analytics: Tools and Technologies 3. Data Analytics: Statistical Approach 4. Supervised and Unsupervised Methods of Machine Learning used in Data Analytics 5. Opportunities and Challenges for Data Analytics Integrated with Machine Learning 6. Cloud Computing: A Change in the IT Infrastructure Landscape 7. Redefining Data Analytics with Machine Learning and Cloud 8. Data Analytics and Cloud together: A powerful combination for E-commerce and Supply Chain logistics 9. Data Analytics, Machine Learning, and Cloud Together: A Powerful Combination for Healthcare & Education 10. Security and Privacy issues for data analytics using machine learning in cloud computing 11. Future Trends for ML-Based Data Analytics in the Cloud

Über Autor(innen)

Dr. Seema Rawat Professor AI & Data Science Innovation & Entrepreneurship

Dr. Seema Rawat, Professor in the Department of Information Technology at Amity School of Engineering and Technology, Amity University Uttar Pradesh Noida, is a distinguished academician and researcher. She has specialization in Deep Learning, Artificial Intelligence, Data Science, Machine Learning, Cloud Computing.

Dr. Seema holds a PhD and M. Tech in Computer Science and Engineering and has 20 years of teaching experience in leading engineering institutes across India and abroad. Dr. Seema has an impressive research portfolio, with high-impact SCIindexed journal papers and Scopus-indexed research papers/book chapters. She has published 70+ research papers, authored books with Elsevier and Springer, and holds more than 15 Indian patents. She serves as a reviewer for top-tier Scopus-indexed journals and editor of various books. She is supervising 5 PhD Scholar in India and 02 Foreign PhD research Scholars.

She is actively involved in professional organizations such as IEEE, ACM, and CSI. Beyond her academic and research accomplishments. Dr. Seema recognized with the Faculty Innovation Excellence Award 2019 by DST, Government of India, she actively contributes to AI research, innovation, and entrepreneurship. Dr. Seema dominates real-world impact as Vice President of UP’s Entrepreneurship Council (WICCI). She is Senior Technical Advisor Technical Advisor to DeetyaSoft, Ennoble IP, and MyDigital360.

Dr. Neelu Jyothi Ahuja Professor & Associate Dean (Academics), School of Computer Science, UPES, Dehradun, Uttarakhand, India

Dr. Neelu Jyothi Ahuja is a professor and associate dean (Academics) at the School of Computer Science, UPES, Dehradun. She earned her PhD in 2010, focusing on developing a rule-based expert system for seismic data interpretation. With 24+ years of experience in teaching, research and project development, she has led numerous AI and machine