Introduction To Data Mining(1st Edition)

Book details

Book Price $0 : The book 'Introduction to Data Mining' by Pang Ning Tan, Michael Steinbach, and Vipin Kumar provides a comprehensive exploration into the foundational methodologies and approaches in the field of data mining. This seminal text is structured to guide readers through an expansive table of content covering crucial areas such as data preprocessing, classification, clustering, and association rule mining. Key technical terms like decision trees, neural networks, and k-means clustering are presented with clarity, making it suitable for both beginners and those with prior knowledge. Rich in examples and practical applications, this book presents a detailed view of algorithms and their real-world relevance. While the authors do not focus on a linear plot or develop characters, their narrative richly develops the landscape of data mining, making complex concepts accessible. The inclusion of a solution manual and answer key enhances its educational use, providing practical exercises and solutions that reinforce learning, making it an invaluable resource for students and practitioners alike. The reception of the book within academic and industry circles highlights its status as a definitive guide in the data mining domain, with its clear explanations and deep insights into large-scale data analysis standing out. Additional Context: Data mining involves dissecting large data sets to identify patterns and establish relationships. It is essential in fields like business intelligence, market analysis, and bioinformatics. Readers benefit from learning programming languages such as Python and R alongside studying key algorithms within this discipline. This engaging narrative offers a cheap and effective way to deepen your understanding of complex themes.