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Discovering Knowledge in Data: An Introduction to Data Mining (Wiley Series on Methods and Applications in Data Mining), by Daniel T. Laro
Download PDF Discovering Knowledge in Data: An Introduction to Data Mining (Wiley Series on Methods and Applications in Data Mining), by Daniel T. Laro
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NOTE: Solution manual is available in the companion site. The link is provided on page 19 in the second paragraph of section 2.3 in the book.
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 techniques. The reader will “learn data mining by doing data mining”. By adding chapters on data modelling preparation, imputation of missing data, and multivariate statistical analysis, Discovering Knowledge in Data, Second Edition remains the eminent reference on 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
- Sales Rank: #50034 in Books
- Published on: 2014-07-08
- Original language: English
- Number of items: 1
- Dimensions: 9.60" h x 1.05" w x 6.40" l, .0 pounds
- Binding: Hardcover
- 336 pages
From the Back Cover
NOTE: Solution manual is available in the companion site. The link is provided on page 19 in the second paragraph of section 2.3
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 techniques. The reader will “learn data mining by doing data mining”. By adding chapters on data modelling preparation, imputation of missing data, and multivariate statistical analysis, Discovering Knowledge in Data, Second Edition remains the eminent reference on data mining. About the Author
Daniel T. Larose earned his PhD in Statistics at the University of Connecticut. He is Professor of Mathematical Sciences and Director of the Data Mining programs at Central Connecticut State University.� His consulting clients have included Microsoft, Forbes Magazine, the CIT Group, KPMG International, Computer Associates, and Deloitte, Inc. This is Larose’s fourth book for Wiley.
Chantal D. Larose is a PhD candidate in Statistics at the University of Connecticut. Her research focuses on the imputation of missing data and model-based clustering. She has taught undergraduate statistics since 2011, and has done statistical consulting for DataMiningConsultant.com, LLC.
Most helpful customer reviews
3 of 3 people found the following review helpful.
Excellent Walkthrough Introduction to Data Science/Data Mining
By Bradley M Chapman
What a great introduction to Data Science! I just completed my undergrad in Applied Mathematics and am beginning a graduate degree in Data Mining. I bought this book because it is necessary for my program. I am surprised at how much I enjoy reading this book. First of all, it is written in a way that informs while not overwhelming. There are plenty of examples and graphics throughout the book that add up to make for a walkthrough more than a talking to. I also like that Dr. Larose is a Statistician. He offers insights that can only be gained from understanding the underlying mathematics behind Data Science. I find that as I read through it, and I work through the R exercises and the Hands On Data exercises, I am becoming more confident and optimistic about my future as a Data Scientist. Of course, further study is necessary, but Discovering Knowledge in Data:... is an excellent beginning.
0 of 1 people found the following review helpful.
Five Stars
By Jordan S
Book was correct and shipped fast
0 of 1 people found the following review helpful.
Five Stars
By Ningchen
Good
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