Overview
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.
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.
- | Author: Avita Katal, Shabana Urooj, Seema Rawat, Praveen Kumar, Neelu Jyothi Ahuja
- | Publisher: Taylor & Francis Ltd
- | Publication Date: Sep 22, 2025
- | Number of Pages:
- | Language:
- | Binding: Hardback
- | ISBN-13: 9781032491462
- | ISBN-10: 1032491469