Đang hiển thị mục 1-20 trong tổng 26

    • Big data, big analytics : emerging business intelligence and analytic trends for today's businesses 

      Minelli, Michael; Chambers, Michele; Dhiraj, Ambiga (John Wiley & Sons, Inc., 2013)
      This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, ...
    • Business intelligence and data mining 

      Maheshwari, Anil K. (Business Expert Press, 2015)
      “This book is a splendid and valuable addition to this subject. The whole book is well written and I have no hesitation to recommend that this can be adapted as a textbook for graduate courses in Business Intelligence and ...
    • Data mining : concepts and techniques 

      Han, Jiawei; Kamber, Micheline; Pei, Jian (Elsevier Inc., 2012)
      This book 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 ...
    • Data mining : concepts, models, methods, and algorithms 

      Kantardzic, Mehmed (Wiley, 2020)
      The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial ...
    • Data mining : practical machine learning tools and techniques 

      Witten, Ian H.; Frank, Eibe; Hall, Mark A.; Pal, Christopher J. (Morgan Kaufmann, 2017)
      This book 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 ...
    • Data mining : practical machine learning tools and techniques 

      Witten, Ian H.; Frank, Eibe; Hall, Mark A. (Morgan Kaufmann, 2011)
      This book 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.
    • Data mining : the textbook 

      Aggarwal, Charu C. (Springer, 2015)
      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 ...
    • Data mining applications for small and medium enterprises 

      Hian, Chye Koh (Centre for Research on Small Enterprise Development Nanyang Technological University, 2005)
    • Data mining for business analytics : concepts, techniques and applications in Python 

      Shmueli, Galit; Bruce, Peter C.; Gedeck, Peter; Patel, Nitin R. (John Wiley & Sons, Inc., 2020)
      "This book supplies insightful, detailed guidance on fundamental data mining techniques. The book guides readers through the use of Python software for developing predictive models and techniques in order to describe and ...
    • Data mining with Microsoft SQL server 2008 

      MacLennan, Jamie; Crivat, Bogdan; Tang, Zhaohui (Wiley Publishing, Inc., 2008)
      Understand how to use the new features of Microsoft SQL Server 2008 for data mining by using the tools in Data Mining with Microsoft SQL Server 2008, which will show you how to use the SQL Server Data Mining Toolset with ...
    • Data science & big data analytics : discovering, analyzing, visualizing and presenting data 

      EMC Education Services (John Wiley & Sons, Inc., 2015)
      "This book is about harnessing the power of data for new insights. The book covers the breadth of activities, methods, and tools that data scientists use. The content focuses on concepts, principles and practical applications ...
    • Handbook of statistical analysis and data mining applications 

      Nisbet, Robert; Miner, Gary; Yale, Ken (Academic Press is an imprint of Elsevier, 2018)
      This book is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. ...
    • Introduction to data mining 

      Tan, Pang-Ning; Steinbach, Michael; Karpatne, Anuj (Pearson, 2019)
    • Introduction to data science : data analysis and prediction algorithms with R 

      Irizarry, Rafael A. (CRC Press, 2019)
      This book introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you ...
    • Mining social media : finding stories in Internet data 

      Vo, Lam Thuy (No Starch Press, Inc., 2020)
      "A guide to mining and analyzing data from social media websites. Combines both practical exercises and conceptual lessons on topics like writing a script to tap into an API and making sense of emoji usage in collected ...
    • Mining the social web 

      Russell, Matthew A.; Klassen, Mikhail (O’Reilly Media, Inc., 2019)
      With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social mediaincluding whos connecting with whom, what theyre talking about, and where theyre ...
    • Principles of data mining 

      Bramer, Max (Springer, 2020)
      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 ...
    • Principles of data mining 

      Bramer, Max (Springer, 2016)
      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 ...
    • Principles of managerial statistics and data science 

      Rivera, Roberto (John Wiley & Sons, Inc., 2020)
      "This book introduces the topics of Big Data, data analytics and data science and features the use of open source data. Among the statistical topics described in this book are: data visualization, descriptive measures, ...