Data Mining For The Masses
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Data Mining For The Masses
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Author : Matthew North
language : en
Publisher:
Release Date : 2012-08-18
Data Mining For The Masses written by Matthew North and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-18 with Data mining categories.
Have you ever found yourself working with a spreadsheet full of data and wishing you could make more sense of the numbers? Have you reviewed sales or operations reports, wondering if there's a better way to anticipate your customers' needs? Perhaps you've even thought to yourself: There's got to be more to these figures than what I'm seeing! Data Mining can help, and you don't need a Ph.D. in Computer Science to do it. You can forecast staffing levels, predict demand for inventory, even sift through millions of lines of customer emails looking for common themes-all using data mining. It's easier than you might think. In Data Mining for the Masses, professor Matt North-a former risk analyst and database developer for eBay.com-uses simple examples, clear explanations and free, powerful, easy-to-use software to teach you the basics of data mining; techniques that can help you answer some of your toughest business questions. You've got data and you know it's got value, if only you can figure out how to unlock it. This book can show you how. Let's start digging! Through an agreement with the Global Text Project, an electronic version of this text is available online at (http://globaltext.terry.uga.edu/books). Proceeds from the sales of printed copies through Amazon enable the author to support the Global Text Project's goal of making electronic texts available to students in developing economies.
Data Mining For The Masses Second Edition
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Author : Matthew North
language : en
Publisher:
Release Date : 2016-01-08
Data Mining For The Masses Second Edition written by Matthew North and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-08 with categories.
We live in a world that generates tremendous amounts of data-more than ever before. In business, and in our personal lives, we use smartphones and tablets, web sites and watches; with dozens of apps and interfaces to shop, learn, entertain and inform. Businesses increasingly use technology to interact with consumers to provide marketing, customer service, product information and more. All of this technological activity generates data-data that can be useful in many ways. Data mining can help to identify interesting patterns and messages that exist, often hidden beneath the surface. In this modern age of information systems, it is easier than ever before to extract meaning from data. From classification to prediction, data mining can help. In Data Mining for the Masses, Second Edition, professor Matt North-a former risk analyst and software engineer at eBay-uses simple examples and clear explanations with free, powerful software tools to teach you the basics of data mining. In this Second Edition, implementations of these examples are offered in both an updated version of the RapidMiner software, and in the popular R Statistical Package. You've got more data than ever before and you know it's got value, if only you can figure out how to get to it. This book can show you how. Let's start digging! Author's Note: The first edition of this text continues to be available for download, free of charge as a PDF file, from the GlobalText online library.
Data Mining Techniques
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Author : Michael J. A. Berry
language : en
Publisher: John Wiley & Sons
Release Date : 2004-04-09
Data Mining Techniques written by Michael J. A. Berry and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-09 with Business & Economics categories.
Many companies have invested in building large databases and data warehouses capable of storing vast amounts of information. This book offers business, sales and marketing managers a practical guide to accessing such information.
Principles Of Data Mining
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Author : Max Bramer
language : en
Publisher: Springer
Release Date : 2016-11-09
Principles Of Data Mining written by Max Bramer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-09 with Computers categories.
This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering. Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail. It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. As an aid to self study, this book aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included. This expanded third edition includes detailed descriptions of algorithms for classifying streaming data, both stationary data, where the underlying model is fixed, and data that is time-dependent, where the underlying model changes from time to time - a phenomenon known as concept drift.
Data Mining And Predictive Analytics
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Author : Daniel T. Larose
language : en
Publisher: John Wiley & Sons
Release Date : 2015-03-16
Data Mining And Predictive Analytics written by Daniel T. Larose and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-16 with Computers categories.
Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.
Principles Of Data Mining
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Author : David J. Hand
language : en
Publisher: MIT Press
Release Date : 2001-08-17
Principles Of Data Mining written by David J. Hand and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-08-17 with Computers categories.
The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.
Next Generation Of Data Mining Applications
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Author : Mehmed Kantardzic
language : en
Publisher: Wiley-IEEE Press
Release Date : 2005-03-08
Next Generation Of Data Mining Applications written by Mehmed Kantardzic and has been published by Wiley-IEEE Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-03-08 with Computers categories.
Discover the next generation of data-mining tools and technology This book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in: Industry and business Science and engineering Bioinformatics and biotechnology Medicine and pharmaceuticals Web and text-mining Security New trends in data-mining technology And much more . . . Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover: New data-mining tools to automate the evaluation and qualification of sales opportunities The latest tools needed for gene mapping and proteomic data analysis Sophisticated techniques that can be engaged in crime fighting and prevention With its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making sense of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics.
Data Mining Concepts And Techniques
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Author : Jiawei Han
language : en
Publisher: Elsevier
Release Date : 2011-06-09
Data Mining Concepts And Techniques written by Jiawei Han and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-09 with Computers categories.
Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. - Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects - Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields - Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
Predictive Analytics And Data Mining
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Author : Vijay Kotu
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-11-27
Predictive Analytics And Data Mining written by Vijay Kotu and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-27 with Computers categories.
Put Predictive Analytics into ActionLearn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining.You’ll be able to:1. Gain the necessary knowledge of different data mining techniques, so that you can select the right technique for a given data problem and create a general purpose analytics process.2. Get up and running fast with more than two dozen commonly used powerful algorithms for predictive analytics using practical use cases.3. Implement a simple step-by-step process for predicting an outcome or discovering hidden relationships from the data using RapidMiner, an open source GUI based data mining tool Predictive analytics and Data Mining techniques covered: Exploratory Data Analysis, Visualization, Decision trees, Rule induction, k-Nearest Neighbors, Naïve Bayesian, Artificial Neural Networks, Support Vector machines, Ensemble models, Bagging, Boosting, Random Forests, Linear regression, Logistic regression, Association analysis using Apriori and FP Growth, K-Means clustering, Density based clustering, Self Organizing Maps, Text Mining, Time series forecasting, Anomaly detection and Feature selection. Implementation files can be downloaded from the book companion site at www.LearnPredictiveAnalytics.com Demystifies data mining concepts with easy to understand language Shows how to get up and running fast with 20 commonly used powerful techniques for predictive analysis Explains the process of using open source RapidMiner tools Discusses a simple 5 step process for implementing algorithms that can be used for performing predictive analytics Includes practical use cases and examples
The History Manifesto
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Author : Jo Guldi
language : en
Publisher: Cambridge University Press
Release Date : 2014-10-02
The History Manifesto written by Jo Guldi and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-02 with Political Science categories.
How should historians speak truth to power – and why does it matter? Why is five hundred years better than five months or five years as a planning horizon? And why is history – especially long-term history – so essential to understanding the multiple pasts which gave rise to our conflicted present? The History Manifesto is a call to arms to historians and everyone interested in the role of history in contemporary society. Leading historians Jo Guldi and David Armitage identify a recent shift back to longer-term narratives, following many decades of increasing specialisation, which they argue is vital for the future of historical scholarship and how it is communicated. This provocative and thoughtful book makes an important intervention in the debate about the role of history and the humanities in a digital age. It will provoke discussion among policymakers, activists and entrepreneurs as well as ordinary listeners, viewers, readers, students and teachers. This title is also available as Open Access.