Data Mining

<p><strong style=background-color: rgba(255 255 255 1); color: rgba(51 51 51 1)>Data Mining: Methodologies and Applications</strong><span style=background-color: rgba(255 255 255 1); color: rgba(51 51 51 1)> presents a comprehensive yet accessible introduction to data mining-a key area of artificial intelligence focused on uncovering patterns and insights from datasets using machine learning techniques. This textbook addresses a gap in existing literature by offering a clear balanced approach that integrates theoretical foundations with real-world applications.</span></p><p></p><p><span style=background-color: rgba(255 255 255 1); color: rgba(51 51 51 1)>Core topics include essential data mining methods such as regression classification clustering and association analysis. The book goes beyond algorithm application to explain how and why these techniques work equipping students with the knowledge needed to make informed decisions in data-driven environments.</span></p><p></p><p><span style=background-color: rgba(255 255 255 1); color: rgba(51 51 51 1)>Designed for advanced undergraduate and graduate students particularly in engineering computer science and related STEM fields this book includes hands-on exercises case studies and projects. These features reinforce concepts and challenge readers to apply data mining methods to realistic problems-preparing them for the demands of AI-driven industries.</span></p><p></p><p><span style=background-color: rgba(255 255 255 1); color: rgba(51 51 51 1)>As artificial intelligence becomes increasingly integral to modern innovation this book serves as a timely and practical guide for learners seeking to understand the methods that power intelligent systems.</span></p>