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Quantitative Analysis for System Applications: Data Science and Analytics Tools and Techniques, Daniel A McGrath


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Автор: Daniel A McGrath
Название:  Quantitative Analysis for System Applications: Data Science and Analytics Tools and Techniques
ISBN: 9781634624237
Издательство: Gazelle Book Services
Классификация:


ISBN-10: 1634624238
Обложка/Формат: Paperback
Страницы: 294
Вес: 0.79 кг.
Дата издания: 15.09.2018
Серия: Computing & IT
Язык: English
Размер: 218 x 279 x 20
Читательская аудитория: General (us: trade)
Ключевые слова: Data warehousing,Data mining,Computer modelling & simulation,Artificial intelligence
Подзаголовок: Data science and analytics tools and techniques
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Поставляется из: Англии
Описание:

As data holdings get bigger and questions get harder, data scientists and analysts must focus on the systems, the tools and techniques, and the disciplined process to get the correct answer, quickly Whether you work within industry or government, this book will provide you with a foundation to successfully and confidently process large amounts of quantitative data.

Here are just a dozen of the many questions answered within these pages:

  1. What does quantitative analysis of a system really mean?
  2. What is a system?
  3. What are big data and analystics?
  4. How do you know your numbers are good?
  5. What will the future data science environment look like?
  6. How do you determine data provenance?
  7. How do you gather and process information, and then organize, store, and synthesize it?
  8. How does an organization implement data analytics?
  9. Do you really need to think like a Chief Information Officer?
  10. What is the best way to protect data?
  11. What makes a good dashboard?
  12. What is the relationship between eating ice cream and getting attacked by a shark?

The nine chapters in this book are arranged in three parts that address systems concepts in general, tools and techniques, and future trend topics. Systems concepts include contrasting open and closed systems, performing data mining and big data analysis, and gauging data quality. Tools and techniques include analyzing both continuous and discrete data, applying probability basics, and practicing quantitative analysis such as descriptive and inferential statistics. Future trends include leveraging the Internet of Everything, modeling Artificial Intelligence, and establishing a Data Analytics Support Office (DASO).

Many examples are included that were generated using common software, such as Excel, Minitab, Tableau, SAS, and Crystal Ball. While words are good, examples can sometimes be a better teaching tool. For each example included, data files can be found on the companion website. Many of the data sets are tied to the global economy because they use data from shipping ports, air freight hubs, largest cities, and soccer teams. The appendices contain more detailed analysis including the 10 Ts for Data Mining, Million Row Data Audit (MRDA) Processes, Analysis of Rainfall, and Simulation Models for Evaluating Traffic Flow.




Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.

Автор: Witten, Ian H.
Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.
ISBN: 0128042915 ISBN-13(EAN): 9780128042915
Издательство: Elsevier Science
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Цена: 9262.00 р.
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Описание:

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.

Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.

Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.

It contains

  • Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
  • Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
  • Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.

  • Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
  • Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
  • Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
  • Includes open-access online courses that introduce practical applications of the material in the book
Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner

Автор: Galit Shmueli, Peter C. Bruce, Nitin R. Patel
Название: Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner
ISBN: 1118729277 ISBN-13(EAN): 9781118729274
Издательство: Wiley
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Цена: 17741.00 р.
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Описание: Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies.

Data Mining: Tools, Techniques, Frameworks and Applications

Автор: Benson Mick
Название: Data Mining: Tools, Techniques, Frameworks and Applications
ISBN: 1682850005 ISBN-13(EAN): 9781682850008
Издательство: Неизвестно
Цена: 20116.00 р.
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Описание: Data mining is an important branch of computer science and information technology management that deals with the discovery and analysis of datasets. This book covers in detail some existent theories as well as innovative concepts revolving around data mining such as bio data analytics, analysis of social structures and patterns, correlations and fluctuations, etc. With its detailed analyses and data, this book will prove immensely beneficial to professionals and students involved in this area at various levels.

Data Mining: Practical Machine Learning Tools and Techniques,

Автор: Ian H. Witten
Название: Data Mining: Practical Machine Learning Tools and Techniques,
ISBN: 0123748569 ISBN-13(EAN): 9780123748560
Издательство: Elsevier Science
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Цена: 8695.00 р.
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Описание: Like the popular second edition, Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining?including both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. <br><br>Complementing the book is a fully functional platform-independent open source Weka software for machine learning, available for free download. <br><br>The book is a major revision of the second edition that appeared in 2005. While the basic core remains the same, it has been updated to reflect the changes that have taken place over the last four or five years. The highlights for the updated new edition include completely revised technique sections; new chapter on Data Transformations, new chapter on Ensemble Learning, new chapter on Massive Data Sets, a new ?book release? version of the popular Weka machine learning open source software (developed by the authors and specific to the Third Edition); new material on ?multi-instance learning?; new information on ranking the classification, plus comprehensive updates and modernization throughout. All in all, approximately 100 pages of new material.<br> <br><br>* Thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques<br><br>* Algorithmic methods at the heart of successful data mining?including tired and true methods as well as leading edge methods<br><br>* Performance improvement techniques that work by transforming the input or output<br><br>* Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization?in an updated, interactive interface. <br>

Intelligent Data analysis and its Applications, Volume II

Автор: Jeng-Shyang Pan; Vaclav Snasel; Emilio S. Corchado
Название: Intelligent Data analysis and its Applications, Volume II
ISBN: 3319077724 ISBN-13(EAN): 9783319077727
Издательство: Springer
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Цена: 32142.00 р.
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Описание: This volume presents the proceedings of the First Euro-China Conference on Intelligent Data Analysis and Applications (ECC 2014), which was hosted by Shenzhen Graduate School of Harbin Institute of Technology and was held in Shenzhen City on June 13-15, 2014.

Cognitive Social Mining Applications in Data Analytics and Forensics

Автор: Anandakumar Haldorai, Arulmurugan Ramu
Название: Cognitive Social Mining Applications in Data Analytics and Forensics
ISBN: 1522575227 ISBN-13(EAN): 9781522575221
Издательство: Mare Nostrum (Eurospan)
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Цена: 28413.00 р.
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Описание: Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data.Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals.

Model Order Reduction Techniques with Applications in Finite Element Analysis

Автор: Zu-Qing Qu
Название: Model Order Reduction Techniques with Applications in Finite Element Analysis
ISBN: 1849969248 ISBN-13(EAN): 9781849969246
Издательство: Springer
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Цена: 23058.00 р.
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Описание: Winner of the 2003 Thomas and Znaniecki Award, this book based on extensive research in all of the major Israeli communities including New York, Paris and London, looks at their reasons for leaving, their relations with Israelis who have not left and with the Jewish and non-Jewish communities in the countries in which they settle, as well as those who after years of emigration, decide to return.

Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining

Автор: Emmanouil Amolochitis
Название: Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining
ISBN: 8793609647 ISBN-13(EAN): 9788793609648
Издательство: Taylor&Francis
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Цена: 11789.00 р.
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Описание: Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining presents novel algorithms for academic search, recommendation and association rule mining that have been developed and optimized for different commercial as well as academic purpose systems. Along with the design and implementation of algorithms, a major part of the work presented in the book involves the development of new systems both for commercial as well as for academic use. In the first part of the book the author introduces a novel hierarchical heuristic scheme for re-ranking academic publications retrieved from standard digital libraries. The scheme is based on the hierarchical combination of a custom implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. In order to evaluate the performance of the introduced algorithms, a meta-search engine has been designed and developed that submits user queries to standard digital repositories of academic publications and re-ranks the top-n results using the introduced hierarchical heuristic scheme. In the second part of the book the design of novel recommendation algorithms with application in different types of e-commerce systems are described. The newly introduced algorithms are a part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. The initial version of the system uses a novel hybrid recommender (user, item and content based) and provides daily recommendations to all active subscribers of the provider (currently more than 30,000). The recommenders that we are presenting are hybrid by nature, using an ensemble configuration of different content, user as well as item-based recommenders in order to provide more accurate recommendation results.The final part of the book presents the design of a quantitative association rule mining algorithm. Quantitative association rules refer to a special type of association rules of the form that antecedent implies consequent consisting of a set of numerical or quantitative attributes. The introduced mining algorithm processes a specific number of user histories in order to generate a set of association rules with a minimally required support and confidence value. The generated rules show strong relationships that exist between the consequent and the antecedent of each rule, representing different items that have been consumed at specific price levels. This research book will be of appeal to researchers, graduate students, professionals, engineers and computer programmers.

Developing Churn Models Using Data Mining Techniques And Social Network Analysis

Автор: Klepac, Kopal & Mrsic
Название: Developing Churn Models Using Data Mining Techniques And Social Network Analysis
ISBN: 1466662883 ISBN-13(EAN): 9781466662889
Издательство: Mare Nostrum (Eurospan)
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Цена: 27027.00 р.
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Описание: Churn prediction, recognition, and mitigation have become essential topics in various industries. As a means for forecasting and manageing risk, further research in this field can greatly assist companies in making informed decisions based on future possible scenarios.Developing Churn Models Using Data Mining Techniques and Social Network Analysis provides an in-depth analysis of attrition modeling relevant to business planning and management. Through its insightful and detailed explanation of best practices, tools, and theory surrounding churn prediction and the integration of analytics tools, this publication is especially relevant to managers, data specialists, business analysts, academicians, and upper-level students.

PowerFactory Applications for Power System Analysis

Автор: Francisco M. Gonzalez-Longatt; Jos? Luis Rueda
Название: PowerFactory Applications for Power System Analysis
ISBN: 3319129570 ISBN-13(EAN): 9783319129570
Издательство: Springer
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Цена: 19564.00 р.
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Описание: This book presents a comprehensive set of guidelines and applications of DIgSILENT PowerFactory, an advanced power system simulation software package, for different types of power systems studies.

Optimization Techniques and Applications with Examples

Автор: Yang
Название: Optimization Techniques and Applications with Examples
ISBN: 1119490545 ISBN-13(EAN): 9781119490548
Издательство: Wiley
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Цена: 16466.00 р.
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Описание:

A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and computer sciences

Optimization Techniques and Applications with Examples introduces the fundamentals of all the commonly used techniques in optimization that encompass the broadness and diversity of the methods (traditional and new) and algorithms. The author--a noted expert in the field--covers a wide range of topics including mathematical foundations, optimization formulation, optimality conditions, algorithmic complexity, linear programming, convex optimization, and integer programming. In addition, the book discusses artificial neural network, clustering and classifications, constraint-handling, queueing theory, support vector machine and multi-objective optimization, evolutionary computation, nature-inspired algorithms and many other topics.

Designed as a practical resource, all topics are explained in detail with step-by-step examples to show how each method works. The book's exercises test the acquired knowledge that can be potentially applied to real problem solving. By taking an informal approach to the subject, the author helps readers to rapidly acquire the basic knowledge in optimization, operational research, and applied data mining. This important resource:

  • Offers an accessible and state-of-the-art introduction to the main optimization techniques
  • Contains both traditional optimization techniques and the most current algorithms and swarm intelligence-based techniques
  • Presents a balance of theory, algorithms, and implementation
  • Includes more than 100 worked examples with step-by-step explanations

Written for upper undergraduates and graduates in a standard course on optimization, operations research and data mining, Optimization Techniques and Applications with Examples is a highly accessible guide to understanding the fundamentals of all the commonly used techniques in optimization.

Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence

Автор: Shrawan Kumar Trivedi, Shubhamoy Dey, Anil Kumar, Tapan Kumar Panda
Название: Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence
ISBN: 1522520317 ISBN-13(EAN): 9781522520313
Издательство: Mare Nostrum (Eurospan)
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Цена: 37838.00 р.
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Описание: Presents the latest advances in business applications and the use of mining software solutions to achieve optimal decision-making and risk management results. Highlighting innovative studies on data warehousing, business activity monitoring, and text mining, this publication is an ideal reference source for research scholars, management faculty, and practitioners.


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