Applied Machine Learning – From Cyber Security to Medical Diagnosis

This book is designed as a practical and application-oriented introduction to machine learning, with a strong focus on real-world domains such as financial fraud detection, medical diagnosis, and customer analytics. Rather than presenting machine learning only through theory, the book emphasizes hands-on learning, real datasets, and practical scenarios that allow readers to understand how machine learning techniques are implemented in real environments.
The chapters are structured in a progressive manner so that readers can move from foundational concepts to more advanced applications and practical implementations. Each chapter combines conceptual explanations, diagrams, case studies, and Python-based exercises so that readers can develop both theoretical understanding and practical skills.
The book currently consists of nine chapters, each designed to address a specific aspect of machine learning and its applications.