Data Mining: Concepts, Techniques and Applications

Data mining is the process of discovering patterns, correlations, and insights from large datasets to extract valuable information. It comprises a variety of techniques and methods aimed at uncovering hidden patterns and relationships within data. Theoretically, data mining involves several key components such as data pre-processing, where raw data is cleaned and prepared for analysis, followed by the application of various algorithms and models to identify patterns. Techniques like clustering, classification, regression, and association rule mining are commonly used in this process. Data mining finds applications across various domains including business, healthcare, finance, marketing, and more. In business, it aids in customer segmentation, market basket analysis, and fraud detection. In healthcare, it helps in disease diagnosis, patient monitoring, and drug discovery. Moreover, data mining techniques are essential for predictive analytics, allowing organizations to forecast future trends and make informed decisions. The objective of this book is to give a general view of the different areas of data mining, and its applications. The topics included in this book are of utmost significance and bound to provide incredible insights to the readers. For all those who are interested in data mining, this book can prove to be an essential guide.