Daniel T.Larose – Discovering Knowledge in Data
Daniel T.Larose – Discovering Knowledge in Data
Daniel T.Larose – Discovering Knowledge in Data
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Description
DANIEL T.LAROSE – DISCOVERING KNOWLEDGE IN DATA
Business intelligence, statistical analysis, and data mining are part of the field of data mining. The process of discovering knowledge in data is more relevant than it has ever been 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 tools needed to thrive in the big data world are provided in this book. The author shows how to leverage a company’s existing databases to increase profits and market share, and explains the most current data science methods and techniques. The reader will learn how to do data mining. Chapter additions include data modelling preparation, imputation of missing data, and multivariate statistical analysis. The second edition of discovering knowledge in data. There is a reference to data mining. .
- The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis.
- Includes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and Visualization
- Offers extensive coverage of the R statistical programming language
- Contains 280 end-of-chapter exercises
- Includes a companion website with further resources for all readers, and Powerpoint slides, a solutions manual, and suggested projects for instructors who adopt the book
Daniel T.Larose is the author of Discovering Knowledge in Data and Discovering Knowledge in Data Review.
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