Authors: Mrs. Rajrupa Metia, Ms. Jeyarani R, Dr. P. Anandan and Dr. V. Sathya

ISBN: 978-81-995936-9-5

DOI: https://doi.org/10.59646/527

Date of Publication: December 03, 2025

About the Book: 

Applied Machine Learning: Concepts and Techniques is written as a comprehensive, structured, and application-driven guide for students, researchers, and professionals seeking mastery over the foundational and advanced principles of machine learning. As machine learning becomes deeply integrated into scientific research, business innovation, and societal decision-making, the need for clear, rigorous, and practice-oriented learning materials grows significantly. This book addresses that need by blending mathematical intuition, algorithmic depth, and real-world relevance into a cohesive learning journey. Beginning with the core ideas of what it means for a machine to learn, the chapters progress through supervised and unsupervised learning, regression and classification frameworks, preprocessing pipelines, clustering models, neural networks, and practical case studies. Each section is designed to demystify complex concepts using step-by-step derivations, comparative analyses, detailed algorithms, and intuitive explanations, ensuring accessibility without sacrificing academic rigor. Beyond theoretical understanding, this book emphasizes implementation, interpretability, and responsible use of machine learning systems—skills crucial for modern practitioners. By the end of this text, readers will not only understand how algorithms work but also why they work, when to apply them, and how to optimize them for real-world performance. It is my hope that this work becomes a valuable companion on your journey into the evolving and exciting field of machine learning, inspiring deeper inquiry, experimentation, and innovation.