Introduction to Data Mining and Analytics

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Publisher : Jones & Bartlett Learning
ISBN 13 : 1284210480
Total Pages : 687 pages
Book Rating : 4.84/5 ( download)

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Book Synopsis Introduction to Data Mining and Analytics by : Kris Jamsa

Download or read book Introduction to Data Mining and Analytics written by Kris Jamsa and published by Jones & Bartlett Learning. This book was released on 2020-02-03 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Analytics provides a broad and interactive overview of a rapidly growing field. The exponentially increasing rate at which data is generated creates a corresponding need for professionals who can effectively handle its storage, analysis, and translation.

Data Mining and Analysis

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Publisher : Cambridge University Press
ISBN 13 : 0521766338
Total Pages : 607 pages
Book Rating : 4.33/5 ( download)

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Book Synopsis Data Mining and Analysis by : Mohammed J. Zaki

Download or read book Data Mining and Analysis written by Mohammed J. Zaki and published by Cambridge University Press. This book was released on 2014-05-12 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of data mining from an algorithmic perspective, integrating related concepts from machine learning and statistics.

Cluster Analysis and Data Mining

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Publisher : Mercury Learning and Information
ISBN 13 : 1942270135
Total Pages : 300 pages
Book Rating : 4.33/5 ( download)

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Book Synopsis Cluster Analysis and Data Mining by : Ronald S. King

Download or read book Cluster Analysis and Data Mining written by Ronald S. King and published by Mercury Learning and Information. This book was released on 2015-05-12 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cluster analysis is used in data mining and is a common technique for statistical data analysis used in many fields of study, such as the medical & life sciences, behavioral & social sciences, engineering, and in computer science. Designed for training industry professionals or for a course on clustering and classification, it can also be used as a companion text for applied statistics. No previous experience in clustering or data mining is assumed. Informal algorithms for clustering data and interpreting results are emphasized. In order to evaluate the results of clustering and to explore data, graphical methods and data structures are used for representing data. Throughout the text, examples and references are provided, in order to enable the material to be comprehensible for a diverse audience. A companion disc includes numerous appendices with programs, data, charts, solutions, etc. eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected]. FEATURES *Places emphasis on illustrating the underlying logic in making decisions during the cluster analysis *Discusses the related applications of statistic, e.g., Ward’s method (ANOVA), JAN (regression analysis & correlational analysis), cluster validation (hypothesis testing, goodness-of-fit, Monte Carlo simulation, etc.) *Contains separate chapters on JAN and the clustering of categorical data *Includes a companion disc with solutions to exercises, programs, data sets, charts, etc.

Data Mining and Machine Learning

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Publisher : Cambridge University Press
ISBN 13 : 1108658695
Total Pages : 780 pages
Book Rating : 4.90/5 ( download)

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Book Synopsis Data Mining and Machine Learning by : Mohammed J. Zaki

Download or read book Data Mining and Machine Learning written by Mohammed J. Zaki and published by Cambridge University Press. This book was released on 2020-01-30 with total page 780 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts. New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning.

Introduction to Data Mining

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Publisher : Pearson Education India
ISBN 13 : 9332586055
Total Pages : 780 pages
Book Rating : 4.55/5 ( download)

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Book Synopsis Introduction to Data Mining by : Pang-Ning Tan

Download or read book Introduction to Data Mining written by Pang-Ning Tan and published by Pearson Education India. This book was released on 2016 with total page 780 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. Each major topic is organized into two chapters, beginni

A General Introduction to Data Analytics

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Publisher : John Wiley & Sons
ISBN 13 : 1119296250
Total Pages : 352 pages
Book Rating : 4.56/5 ( download)

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Book Synopsis A General Introduction to Data Analytics by : João Moreira

Download or read book A General Introduction to Data Analytics written by João Moreira and published by John Wiley & Sons. This book was released on 2018-07-02 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-to-understand terms and does not require familiarity with statistics or programming. The authors—noted experts in the field—highlight an explanation of the intuition behind the basic data analytics techniques. The text also contains exercises and illustrative examples. Thought to be easily accessible to non-experts, the book provides motivation to the necessity of analyzing data. It explains how to visualize and summarize data, and how to find natural groups and frequent patterns in a dataset. The book also explores predictive tasks, be them classification or regression. Finally, the book discusses popular data analytic applications, like mining the web, information retrieval, social network analysis, working with text, and recommender systems. The learning resources offer: A guide to the reasoning behind data mining techniques A unique illustrative example that extends throughout all the chapters Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts Together with these learning resources, the book can be used in a 13-week course guide, one chapter per course topic. The book was written in a format that allows the understanding of the main data analytics concepts by non-mathematicians, non-statisticians and non-computer scientists interested in getting an introduction to data science. A General Introduction to Data Analytics is a basic guide to data analytics written in highly accessible terms.

Introduction to Data Mining and Analytics

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Author :
Publisher : Jones & Bartlett Learning
ISBN 13 : 1284180905
Total Pages : 687 pages
Book Rating : 4.09/5 ( download)

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Book Synopsis Introduction to Data Mining and Analytics by : Kris Jamsa

Download or read book Introduction to Data Mining and Analytics written by Kris Jamsa and published by Jones & Bartlett Learning. This book was released on 2020-02-03 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Analytics provides a broad and interactive overview of a rapidly growing field. The exponentially increasing rate at which data is generated creates a corresponding need for professionals who can effectively handle its storage, analysis, and translation.

Discovering Knowledge in Data

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Publisher : John Wiley & Sons
ISBN 13 : 0471687537
Total Pages : 240 pages
Book Rating : 4.35/5 ( download)

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Book Synopsis Discovering Knowledge in Data by : Daniel T. Larose

Download or read book Discovering Knowledge in Data written by Daniel T. Larose and published by John Wiley & Sons. This book was released on 2005-01-28 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn Data Mining by doing data mining Data mining can be revolutionary-but only when it's done right. The powerful black box data mining software now available can produce disastrously misleading results unless applied by a skilled and knowledgeable analyst. Discovering Knowledge in Data: An Introduction to Data Mining provides both the practical experience and the theoretical insight needed to reveal valuable information hidden in large data sets. Employing a "white box" methodology and with real-world case studies, this step-by-step guide walks readers through the various algorithms and statistical structures that underlie the software and presents examples of their operation on actual large data sets. Principal topics include: * Data preprocessing and classification * Exploratory analysis * Decision trees * Neural and Kohonen networks * Hierarchical and k-means clustering * Association rules * Model evaluation techniques Complete with scores of screenshots and diagrams to encourage graphical learning, Discovering Knowledge in Data: An Introduction to Data Mining gives students in Business, Computer Science, and Statistics as well as professionals in the field the power to turn any data warehouse into actionable knowledge. An Instructor's Manual presenting detailed solutions to all the problems in the book is available online.

Introduction to Data Mining

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Publisher :
ISBN 13 : 9780273769224
Total Pages : 864 pages
Book Rating : 4.27/5 ( download)

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Book Synopsis Introduction to Data Mining by : Pang-Ning Tan

Download or read book Introduction to Data Mining written by Pang-Ning Tan and published by . This book was released on 2018-04-13 with total page 864 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

Introduction to Data Mining and its Applications

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Author :
Publisher : Springer
ISBN 13 : 3540343512
Total Pages : 836 pages
Book Rating : 4.16/5 ( download)

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Book Synopsis Introduction to Data Mining and its Applications by : S. Sumathi

Download or read book Introduction to Data Mining and its Applications written by S. Sumathi and published by Springer. This book was released on 2006-10-12 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, neural networks, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization.