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The field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. Due to the ever-increasing complexity and size of data sets and the wide range of applications in computer science, business, and health care, the process of discovering knowledge in data is more relevant than ever before.

This book provides the tools needed to thrive in today's big data world. The author demonstrates how to leverage a company's existing databases to increase profits and market share, and carefully explains the most current data science methods and...

This book introduces the reader to methods of data mining on the web, including uncovering patterns in web content (classification, clustering, language processing), structure (graphs, hubs, metrics), and usage (modeling, sequence analysis, performance).

Dan Larose's Discovering Statistics is the ideal text for instructors who want to teach the basics of statistical computation as well as how to interpret and apply the results of those computations. Using real data, contemporary examples, step-by-step solutions, extensive pedagogy, and support for common statistical software options, the text familiarizes students with essential computational skills, while helping them build the conceptual understanding needed to interpret and explain their findings. As a result, Discovering Statistics helps students develop a solid and lasting...