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.