Data Mining for Business Analytics

Written By Galit Shmueli
Data Mining for Business Analytics
  • Publsiher : John Wiley & Sons
  • Release : 05 November 2019
  • ISBN : 1119549841
  • Pages : 608 pages
  • Rating : 4/5 from 21 reviews
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Read or download book entitled Data Mining for Business Analytics written by Galit Shmueli which was release on 05 November 2019, this book published by John Wiley & Sons. Available in PDF, EPUB and Kindle Format. Book excerpt: Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R

Data Mining for Business Analytics

Data Mining for Business Analytics
  • Author : Galit Shmueli,Peter C. Bruce,Peter Gedeck,Nitin R. Patel
  • Publisher : John Wiley & Sons
  • Release Date : 2019-11-05
  • Total pages : 608
  • ISBN : 1119549841
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Summary : Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems ...

Data Mining Concepts and Techniques

Data Mining  Concepts and Techniques
  • Author : Jiawei Han,Jian Pei,Micheline Kamber
  • Publisher : Elsevier
  • Release Date : 2011-06-09
  • Total pages : 744
  • ISBN : 1119549841
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Summary : 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). ...

Computational Intelligence in Data Mining

Computational Intelligence in Data Mining
  • Author : Giacomo Della Riccia,Rudolf Kruse,Hans-J. Lenz,Hans-Joachim Lenz
  • Publisher : Springer Science & Business Media
  • Release Date : 2000-05-31
  • Total pages : 166
  • ISBN : 1119549841
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Summary : The book aims to merge Computational Intelligence with Data Mining, which are both hot topics of current research and industrial development, Computational Intelligence, incorporates techniques like data fusion, uncertain reasoning, heuristic search, learning, and soft computing. Data Mining focuses on unscrambling unknown patterns or structures in very large data sets. ...

Data Mining Techniques

Data Mining Techniques
  • Author : Michael J. A. Berry,Gordon S. Linoff
  • Publisher : John Wiley & Sons
  • Release Date : 2004-04-09
  • Total pages : 643
  • ISBN : 1119549841
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Summary : 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....

Data Mining

Data Mining
  • Author : Charu C. Aggarwal
  • Publisher : Springer
  • Release Date : 2015-04-13
  • Total pages : 734
  • ISBN : 1119549841
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Summary : This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues. It goes beyond the traditional focus on data mining problems to introduce advanced data types such as text, time ...

Data Preparation for Data Mining

Data Preparation for Data Mining
  • Author : Dorian Pyle
  • Publisher : Morgan Kaufmann
  • Release Date : 1999-04-05
  • Total pages : 540
  • ISBN : 1119549841
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Summary : This book focuses on the importance of clean, well-structured data as the first step to successful data mining. It shows how data should be prepared prior to mining in order to maximize mining performance....

Educational Data Mining

Educational Data Mining
  • Author : Alejandro Peña-Ayala
  • Publisher : Springer
  • Release Date : 2013-11-08
  • Total pages : 468
  • ISBN : 1119549841
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Summary : This book is devoted to the Educational Data Mining arena. It highlights works that show relevant proposals, developments, and achievements that shape trends and inspire future research. After a rigorous revision process sixteen manuscripts were accepted and organized into four parts as follows: · Profile: The first part embraces three chapters ...

Practical Applications of Data Mining

Practical Applications of Data Mining
  • Author : Sang C. Suh
  • Publisher : Jones & Bartlett Publishers
  • Release Date : 2012
  • Total pages : 414
  • ISBN : 1119549841
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Summary : Various topics of data mining techniques are identified and described throughout, including clustering, association rules, rough set theory, probability theory, neural networks, classification, and fuzzy logic. Each of these techniques is explored with a theoretical introduction and its effectiveness is demonstrated with various chapter examples....

Data Mining

Data Mining
  • Author : Jiawei Han,Micheline Kamber
  • Publisher : Morgan Kaufmann
  • Release Date : 2006
  • Total pages : 770
  • ISBN : 1119549841
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Summary : Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote ...

Principles of Data Mining

Principles of Data Mining
  • Author : Max Bramer
  • Publisher : Springer
  • Release Date : 2020-05-21
  • Total pages : 571
  • ISBN : 1119549841
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Summary : 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 ...

Data Mining

Data Mining
  • Author : Mehmed Kantardzic
  • Publisher : John Wiley & Sons
  • Release Date : 2011-08-16
  • Total pages : 552
  • ISBN : 1119549841
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Summary : This book reviews state-of-the-art methodologies and techniques for analyzing enormous quantities of raw data in high-dimensional data spaces, to extract new information for decision making. The goal of this book is to provide a single introductory source, organized in a systematic way, in which we could direct the readers in ...

Data Preprocessing in Data Mining

Data Preprocessing in Data Mining
  • Author : Salvador García,Julián Luengo,Francisco Herrera
  • Publisher : Springer
  • Release Date : 2014-08-30
  • Total pages : 320
  • ISBN : 1119549841
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Summary : Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount ...

Predictive Analytics Data Mining and Big Data

Predictive Analytics  Data Mining and Big Data
  • Author : S. Finlay
  • Publisher : Springer
  • Release Date : 2014-07-01
  • Total pages : 260
  • ISBN : 1119549841
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Summary : This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations....

R Data Mining

R Data Mining
  • Author : Andrea Cirillo
  • Publisher : Packt Publishing Ltd
  • Release Date : 2017-11-29
  • Total pages : 442
  • ISBN : 1119549841
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Summary : Mine valuable insights from your data using popular tools and techniques in R About This Book Understand the basics of data mining and why R is a perfect tool for it. Manipulate your data using popular R packages such as ggplot2, dplyr, and so on to gather valuable business insights ...

Data Mining with Rattle and R

Data Mining with Rattle and R
  • Author : Graham Williams
  • Publisher : Springer
  • Release Date : 2011-02-25
  • Total pages : 374
  • ISBN : 1119549841
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Summary : Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that abound today. In performing data mining many decisions need to be made regarding the choice of methodology, the choice of ...