Data Analytics using Machine Learning Techniques on Cloud Platforms

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

Buch, Englisch, 200 Seiten, Format (B × H): 156 mm x 234 mm

Data Analytics using Machine Learning Techniques on Cloud Platforms examines how machine learning and cloud computing combine to drive data-driven decision-making across industries. Covering ML techniques, cloud-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.

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

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

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