Journeys To Data Mining

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Journeys to Data Mining

Author : Mohamed Medhat Gaber
Publisher : Springer Science & Business Media
ISBN 13 : 3642280471
Total Pages : 241 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Journeys to Data Mining by : Mohamed Medhat Gaber

Download or read book Journeys to Data Mining written by Mohamed Medhat Gaber and published by Springer Science & Business Media. This book was released on 2012-07-20 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining, an interdisciplinary field combining methods from artificial intelligence, machine learning, statistics and database systems, has grown tremendously over the last 20 years and produced core results for applications like business intelligence, spatio-temporal data analysis, bioinformatics, and stream data processing. The fifteen contributors to this volume are successful and well-known data mining scientists and professionals. Although by no means an exhaustive list, all of them have helped the field to gain the reputation and importance it enjoys today, through the many valuable contributions they have made. Mohamed Medhat Gaber has asked them (and many others) to write down their journeys through the data mining field, trying to answer the following questions: 1. What are your motives for conducting research in the data mining field? 2. Describe the milestones of your research in this field. 3. What are your notable success stories? 4. How did you learn from your failures? 5. Have you encountered unexpected results? 6. What are the current research issues and challenges in your area? 7. Describe your research tools and techniques. 8. How would you advise a young researcher to make an impact? 9. What do you predict for the next two years in your area? 10. What are your expectations in the long term? In order to maintain the informal character of their contributions, they were given complete freedom as to how to organize their answers. This narrative presentation style provides PhD students and novices who are eager to find their way to successful research in data mining with valuable insights into career planning. In addition, everyone else interested in the history of computer science may be surprised about the stunning successes and possible failures computer science careers (still) have to offer.

Data Mining Methods and Models

Author : Daniel T. Larose
Publisher : John Wiley & Sons
ISBN 13 : 0471756474
Total Pages : 340 pages
Book Rating : 4.4/5 (717 download)

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Book Synopsis Data Mining Methods and Models by : Daniel T. Larose

Download or read book Data Mining Methods and Models written by Daniel T. Larose and published by John Wiley & Sons. This book was released on 2006-02-02 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apply powerful Data Mining Methods and Models to Leverage your Data for Actionable Results Data Mining Methods and Models provides: * The latest techniques for uncovering hidden nuggets of information * The insight into how the data mining algorithms actually work * The hands-on experience of performing data mining on large data sets Data Mining Methods and Models: * Applies a "white box" methodology, emphasizing an understanding of the model structures underlying the softwareWalks the reader through the various algorithms and provides examples of the operation of the algorithms on actual large data sets, including a detailed case study, "Modeling Response to Direct-Mail Marketing" * Tests the reader's level of understanding of the concepts and methodologies, with over 110 chapter exercises * Demonstrates the Clementine data mining software suite, WEKA open source data mining software, SPSS statistical software, and Minitab statistical software * Includes a companion Web site, www.dataminingconsultant.com, where the data sets used in the book may be downloaded, along with a comprehensive set of data mining resources. Faculty adopters of the book have access to an array of helpful resources, including solutions to all exercises, a PowerPoint(r) presentation of each chapter, sample data mining course projects and accompanying data sets, and multiple-choice chapter quizzes. With its emphasis on learning by doing, this is an excellent textbook for students in business, computer science, and statistics, as well as a problem-solving reference for data analysts and professionals in the field. An Instructor's Manual presenting detailed solutions to all the problems in the book is available onlne.

Data Mining with Rattle and R

Author : Graham Williams
Publisher : Springer Science & Business Media
ISBN 13 : 144199890X
Total Pages : 382 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Data Mining with Rattle and R by : Graham Williams

Download or read book Data Mining with Rattle and R written by Graham Williams and published by Springer Science & Business Media. This book was released on 2011-08-04 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 data, the choice of tools, and the choice of algorithms. Throughout this book the reader is introduced to the basic concepts and some of the more popular algorithms of data mining. With a focus on the hands-on end-to-end process for data mining, Williams guides the reader through various capabilities of the easy to use, free, and open source Rattle Data Mining Software built on the sophisticated R Statistical Software. The focus on doing data mining rather than just reading about data mining is refreshing. The book covers data understanding, data preparation, data refinement, model building, model evaluation, and practical deployment. The reader will learn to rapidly deliver a data mining project using software easily installed for free from the Internet. Coupling Rattle with R delivers a very sophisticated data mining environment with all the power, and more, of the many commercial offerings.

Data Sketches

Author : Nadieh Bremer
Publisher : CRC Press
ISBN 13 : 0429816820
Total Pages : 429 pages
Book Rating : 4.4/5 (298 download)

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Book Synopsis Data Sketches by : Nadieh Bremer

Download or read book Data Sketches written by Nadieh Bremer and published by CRC Press. This book was released on 2021-02-09 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Data Sketches, Nadieh Bremer and Shirley Wu document the deeply creative process behind 24 unique data visualization projects, and they combine this with powerful technical insights which reveal the mindset behind coding creatively. Exploring 12 different themes – from the Olympics to Presidents & Royals and from Movies to Myths & Legends – each pair of visualizations explores different technologies and forms, blurring the boundary between visualization as an exploratory tool and an artform in its own right. This beautiful book provides an intimate, behind-the-scenes account of all 24 projects and shares the authors’ personal notes and drafts every step of the way. The book features: Detailed information on data gathering, sketching, and coding data visualizations for the web, with screenshots of works-in-progress and reproductions from the authors’ notebooks Never-before-published technical write-ups, with beginner-friendly explanations of core data visualization concepts Practical lessons based on the data and design challenges overcome during each project Full-color pages, showcasing all 24 final data visualizations This book is perfect for anyone interested or working in data visualization and information design, and especially those who want to take their work to the next level and are inspired by unique and compelling data-driven storytelling.

Contemporary Perspectives in Data Mining, Volume 2

Author : Kenneth D. Lawrence
Publisher : IAP
ISBN 13 : 1681230895
Total Pages : 237 pages
Book Rating : 4.6/5 (812 download)

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Book Synopsis Contemporary Perspectives in Data Mining, Volume 2 by : Kenneth D. Lawrence

Download or read book Contemporary Perspectives in Data Mining, Volume 2 written by Kenneth D. Lawrence and published by IAP. This book was released on 2015-07-01 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are in marketing (customer loyalty, identifying profitable customers, instore promotions, e-commerce populations); in business (teaching data mining, efficiency of the Chinese automobile industry, moderate asset allocation funds); and techniques (veterinary predictive models, data integrity in the cloud, irregular pattern detection in a mobility network and road safety modeling.)

A Practical Guide to Data Mining for Business and Industry

Author : Andrea Ahlemeyer-Stubbe
Publisher : John Wiley & Sons
ISBN 13 : 1118763378
Total Pages : 323 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis A Practical Guide to Data Mining for Business and Industry by : Andrea Ahlemeyer-Stubbe

Download or read book A Practical Guide to Data Mining for Business and Industry written by Andrea Ahlemeyer-Stubbe and published by John Wiley & Sons. This book was released on 2014-03-31 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest.

Data Journeys in the Sciences

Author : Sabina Leonelli
Publisher : Springer Nature
ISBN 13 : 3030371778
Total Pages : 411 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Data Journeys in the Sciences by : Sabina Leonelli

Download or read book Data Journeys in the Sciences written by Sabina Leonelli and published by Springer Nature. This book was released on 2020-06-29 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This groundbreaking, open access volume analyses and compares data practices across several fields through the analysis of specific cases of data journeys. It brings together leading scholars in the philosophy, history and social studies of science to achieve two goals: tracking the travel of data across different spaces, times and domains of research practice; and documenting how such journeys affect the use of data as evidence and the knowledge being produced. The volume captures the opportunities, challenges and concerns involved in making data move from the sites in which they are originally produced to sites where they can be integrated with other data, analysed and re-used for a variety of purposes. The in-depth study of data journeys provides the necessary ground to examine disciplinary, geographical and historical differences and similarities in data management, processing and interpretation, thus identifying the key conditions of possibility for the widespread data sharing associated with Big and Open Data. The chapters are ordered in sections that broadly correspond to different stages of the journeys of data, from their generation to the legitimisation of their use for specific purposes. Additionally, the preface to the volume provides a variety of alternative “roadmaps” aimed to serve the different interests and entry points of readers; and the introduction provides a substantive overview of what data journeys can teach about the methods and epistemology of research.

Introduction To Data Mining

Author : Chaitanya P Agrawal, Meena Agrawal
Publisher : Educreation Publishing
ISBN 13 :
Total Pages : 114 pages
Book Rating : 4./5 ( download)

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Book Synopsis Introduction To Data Mining by : Chaitanya P Agrawal, Meena Agrawal

Download or read book Introduction To Data Mining written by Chaitanya P Agrawal, Meena Agrawal and published by Educreation Publishing. This book was released on with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a small endeavor to share the journey of getting introduced to a wonderful topic Data Mining. Personally we came across this during the process of evaluating new tools to be included in the post graduate study curricula of the University we are working in. Soon it became a friendly affair to see the power, potential and ease of empowering the databases with concepts of data mining. It has become powerful in rediscovering the hidden values in data base and soon in data warehouse, equally efficiently. The Data mining is a powerful new technology with great potential focusing on the most important information in their data warehouses. It involves extraction of hidden predictive information from large databases with ease and efficiency. It facilitates to make proactive, knowledge-driven decisions and predict future trends and behaviors. Data mining tools move beyond the analyses of past events provided by retrospective tools typical of decision support systems. The automated, prospective analyses offered by data mining tools can answer finding predictive information easily. This small book is an introduction to the basics of data mining. It also introduces the techniques and technologies behind data mining, the impact of artificial intelligence, artificial neural networks, and fuzzy logic et cetera as the basic building blocks for the same. It concludes with common practical applications, trends and its impact on social and computing environment.

Journey to Data Scientist

Author : Kate Strachnyi
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781548984243
Total Pages : 136 pages
Book Rating : 4.9/5 (842 download)

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Book Synopsis Journey to Data Scientist by : Kate Strachnyi

Download or read book Journey to Data Scientist written by Kate Strachnyi and published by Createspace Independent Publishing Platform. This book was released on 2017-11-13 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: When author Kate Strachnyi wanted to learn more about data science, she went straight to the source. In a series of more than twenty interviews, she asks leading data scientists questions about starting in the field and the future of the industry. With their stories, learn about the many different positions available for data scientists, the criteria recruiters look for when hiring, the best options for building your portfolio, the recruitment and interviewing process, the typical workday for a data scientist, the changing industry and its impact on other industries, the wide variety of projects that use data science, and the skills that can complement and improve your work. Strachnyi's interview subjects include team members from some of the world's largest organizations, including LinkedIn, Pinterest, Bloomberg, and IBM. These men and women graciously explain how they fell in love with data science and list the must-have skills that would make you an invaluable member of a team. Their advice gives you invaluable insight into the world of data science and the best ways you yourself can contribute to amazing research projects and the development of new technology.

Building Winning Algorithmic Trading Systems, + Website

Author : Kevin J. Davey
Publisher : John Wiley & Sons
ISBN 13 : 1118778987
Total Pages : 294 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Building Winning Algorithmic Trading Systems, + Website by : Kevin J. Davey

Download or read book Building Winning Algorithmic Trading Systems, + Website written by Kevin J. Davey and published by John Wiley & Sons. This book was released on 2014-07-21 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop your own trading system with practical guidance and expert advice In Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Training, award-winning trader Kevin Davey shares his secrets for developing trading systems that generate triple-digit returns. With both explanation and demonstration, Davey guides you step-by-step through the entire process of generating and validating an idea, setting entry and exit points, testing systems, and implementing them in live trading. You'll find concrete rules for increasing or decreasing allocation to a system, and rules for when to abandon one. The companion website includes Davey's own Monte Carlo simulator and other tools that will enable you to automate and test your own trading ideas. A purely discretionary approach to trading generally breaks down over the long haul. With market data and statistics easily available, traders are increasingly opting to employ an automated or algorithmic trading system—enough that algorithmic trades now account for the bulk of stock trading volume. Building Algorithmic Trading Systems teaches you how to develop your own systems with an eye toward market fluctuations and the impermanence of even the most effective algorithm. Learn the systems that generated triple-digit returns in the World Cup Trading Championship Develop an algorithmic approach for any trading idea using off-the-shelf software or popular platforms Test your new system using historical and current market data Mine market data for statistical tendencies that may form the basis of a new system Market patterns change, and so do system results. Past performance isn't a guarantee of future success, so the key is to continually develop new systems and adjust established systems in response to evolving statistical tendencies. For individual traders looking for the next leap forward, Building Algorithmic Trading Systems provides expert guidance and practical advice.

Contemporary Perspectives in Data Mining

Author : Kenneth D. Lawrence
Publisher : IAP
ISBN 13 : 164802145X
Total Pages : 159 pages
Book Rating : 4.6/5 (48 download)

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Book Synopsis Contemporary Perspectives in Data Mining by : Kenneth D. Lawrence

Download or read book Contemporary Perspectives in Data Mining written by Kenneth D. Lawrence and published by IAP. This book was released on 2021-01-01 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are in business (banking, brokerage, and insurance), marketing (customer relationship, retailing, logistics, and travel), as well as in manufacturing, health care, fraud detection, homeland security and law enforcement.

Journey to Data Quality

Author : Yang W. Lee
Publisher : MIT Press (MA)
ISBN 13 :
Total Pages : 248 pages
Book Rating : 4.4/5 (91 download)

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Book Synopsis Journey to Data Quality by : Yang W. Lee

Download or read book Journey to Data Quality written by Yang W. Lee and published by MIT Press (MA). This book was released on 2006 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: All organizations today confront data quality problems, both systemic and structural. Neither ad hoc approaches nor fixes at the systems level--installing the latest software or developing an expensive data warehouse--solve the basic problem of bad data quality practices. Journey to Data Qualityoffers a roadmap that can be used by practitioners, executives, and students for planning and implementing a viable data and information quality management program. This practical guide, based on rigorous research and informed by real-world examples, describes the challenges of data management and provides the principles, strategies, tools, and techniques necessary to meet them. The authors, all leaders in the data quality field for many years, discuss how to make the economic case for data quality and the importance of getting an organization's leaders on board. They outline different approaches for assessing data, both subjectively (by users) and objectively (using sampling and other techniques). They describe real problems and solutions, including efforts to find the root causes of data quality problems at a healthcare organization and data quality initiatives taken by a large teaching hospital. They address setting company policy on data quality and, finally, they consider future challenges on the journey to data quality.

Data Preparation for Data Mining

Author : Dorian Pyle
Publisher : Morgan Kaufmann
ISBN 13 : 9781558605299
Total Pages : 566 pages
Book Rating : 4.6/5 (52 download)

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Book Synopsis Data Preparation for Data Mining by : Dorian Pyle

Download or read book Data Preparation for Data Mining written by Dorian Pyle and published by Morgan Kaufmann. This book was released on 1999-03-22 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Discovering Knowledge in Data

Author : Daniel T. Larose
Publisher : John Wiley & Sons
ISBN 13 : 0471687537
Total Pages : 240 pages
Book Rating : 4.4/5 (716 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.

Data Mining: Concepts and Techniques

Author : Jiawei Han
Publisher : Elsevier
ISBN 13 : 0123814804
Total Pages : 740 pages
Book Rating : 4.1/5 (238 download)

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Book Synopsis Data Mining: Concepts and Techniques by : Jiawei Han

Download or read book Data Mining: Concepts and Techniques written by Jiawei Han and published by Elsevier. This book was released on 2011-06-09 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Machine Learning and Data Mining

Author : Igor Kononenko
Publisher : Elsevier
ISBN 13 : 0857099442
Total Pages : 475 pages
Book Rating : 4.8/5 (57 download)

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Book Synopsis Machine Learning and Data Mining by : Igor Kononenko

Download or read book Machine Learning and Data Mining written by Igor Kononenko and published by Elsevier. This book was released on 2007-04-30 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. This book has been written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining.Suitable for advanced undergraduates and their tutors at postgraduate level in a wide area of computer science and technology topics as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to the libraries and bookshelves of the many companies who are using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions. Provides an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining A valuable addition to the libraries and bookshelves of companies using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions

Data Mining for Business Analytics

Author : Galit Shmueli
Publisher : John Wiley & Sons
ISBN 13 : 111954985X
Total Pages : 608 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Data Mining for Business Analytics by : Galit Shmueli

Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2019-10-14 with total page 608 pages. Available in PDF, EPUB and Kindle. 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