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.