Computer Data Analysis
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Computer Aided Data Analysis
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Author : William R. Green
language : en
Publisher: Wiley-Interscience
Release Date : 1985-04-23
Computer Aided Data Analysis written by William R. Green and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985-04-23 with Computers categories.
Designed for non-specialist computer users, here is an introduction to the data analysis techniques in common use in the applied sciences. Provides efficient procedures for analyzing a particular set of data, offering clear, complete treatments of the initial steps in computer data analysis, multivariate data analysis, fundamentals of computer plotting, enhanced display techniques, advanced statistical techniques such as geostatistics, and modeling and data interpretation.
Guide To Intelligent Data Analysis
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Author : Michael R. Berthold
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-06-23
Guide To Intelligent Data Analysis written by Michael R. Berthold and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-23 with Computers categories.
Each passing year bears witness to the development of ever more powerful computers, increasingly fast and cheap storage media, and even higher bandwidth data connections. This makes it easy to believe that we can now – at least in principle – solve any problem we are faced with so long as we only have enough data. Yet this is not the case. Although large databases allow us to retrieve many different single pieces of information and to compute simple aggregations, general patterns and regularities often go undetected. Furthermore, it is exactly these patterns, regularities and trends that are often most valuable. To avoid the danger of “drowning in information, but starving for knowledge” the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. However, it is not these tools alone but the intelligent application of human intuition in combination with computational power, of sound background knowledge with computer-aided modeling, and of critical reflection with convenient automatic model construction, that results in successful intelligent data analysis projects. Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems. Topics and features: guides the reader through the process of data analysis, following the interdependent steps of project understanding, data understanding, data preparation, modeling, and deployment and monitoring; equips the reader with the necessary information in order to obtain hands-on experience of the topics under discussion; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; includes numerous examples using R and KNIME, together with appendices introducing the open source software; integrates illustrations and case-study-style examplesto support pedagogical exposition. This practical and systematic textbook/reference for graduate and advanced undergraduate students is also essential reading for all professionals who face data analysis problems. Moreover, it is a book to be used following one’s exploration of it. Dr. Michael R. Berthold is Nycomed-Professor of Bioinformatics and Information Mining at the University of Konstanz, Germany. Dr. Christian Borgelt is Principal Researcher at the Intelligent Data Analysis and Graphical Models Research Unit of the European Centre for Soft Computing, Spain. Dr. Frank Höppner is Professor of Information Systems at Ostfalia University of Applied Sciences, Germany. Dr. Frank Klawonn is a Professor in the Department of Computer Science and Head of the Data Analysis and Pattern Recognition Laboratory at Ostfalia University of Applied Sciences, Germany. He is also Head of the Bioinformatics and Statistics group at the Helmholtz Centre for Infection Research, Braunschweig, Germany.
Sql For Data Analysis
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Author : Cathy Tanimura
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-09-09
Sql For Data Analysis written by Cathy Tanimura and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-09 with Computers categories.
With the explosion of data, computing power, and cloud data warehouses, SQL has become an even more indispensable tool for the savvy analyst or data scientist. This practical book reveals new and hidden ways to improve your SQL skills, solve problems, and make the most of SQL as part of your workflow. You'll learn how to use both common and exotic SQL functions such as joins, window functions, subqueries, and regular expressions in new, innovative ways--as well as how to combine SQL techniques to accomplish your goals faster, with understandable code. If you work with SQL databases, this is a must-have reference. Learn the key steps for preparing your data for analysis Perform time series analysis using SQL's date and time manipulations Use cohort analysis to investigate how groups change over time Use SQL's powerful functions and operators for text analysis Detect outliers in your data and replace them with alternate values Establish causality using experiment analysis, also known as A/B testing
Concept Data Analysis
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Author : Claudio Carpineto
language : en
Publisher: John Wiley & Sons
Release Date : 2004-10-22
Concept Data Analysis written by Claudio Carpineto 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 2004-10-22 with Computers categories.
With the advent of the Web along with the unprecedented amount of information available in electronic format, conceptual data analysis is more useful and practical than ever, because this technology addresses important limitations of the systems that currently support users in their quest for information. Concept Data Analysis: Theory & Applications is the first book that provides a comprehensive treatment of the full range of algorithms available for conceptual data analysis, spanning creation, maintenance, display and manipulation of concept lattices. The accompanying website allows you to gain a greater understanding of the principles covered in the book through actively working on the topics discussed. The three main areas explored are interactive mining of documents or collections of documents (including Web documents), automatic text ranking, and rule mining from structured data. The potentials of conceptual data analysis in the application areas being considered are further illustrated by two detailed case studies. Concept Data Analysis: Theory & Applications is essential for researchers active in information processing and management and industry practitioners who are interested in creating a commercial product for conceptual data analysis or developing content management applications.
Computer Data Analysis
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Author :
language : en
Publisher:
Release Date :
Computer Data Analysis written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Computer Aided Testing And Modal Analysis
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Author : Society for Experimental Mechanics (U.S.). Fall Conference
language : en
Publisher:
Release Date : 1984
Computer Aided Testing And Modal Analysis written by Society for Experimental Mechanics (U.S.). Fall Conference and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Materials categories.
Data Science And Big Data Analytics
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Author : EMC Education Services
language : en
Publisher: John Wiley & Sons
Release Date : 2014-12-19
Data Science And Big Data Analytics written by EMC Education Services 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 2014-12-19 with Computers categories.
Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!
U S Government Research Development Reports
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Author :
language : en
Publisher:
Release Date : 1970
U S Government Research Development Reports written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1970 with Science categories.
Data Analysis For Social Science
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Author : Elena Llaudet
language : en
Publisher: Princeton University Press
Release Date : 2022-11-29
Data Analysis For Social Science written by Elena Llaudet and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-29 with Computers categories.
"Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--
High Performance Big Data Analytics
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Author : Pethuru Raj
language : en
Publisher: Springer
Release Date : 2015-10-16
High Performance Big Data Analytics written by Pethuru Raj and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-16 with Computers categories.
This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in every chapter; presents detailed case studies on social media analytics for intelligent businesses and on big data analytics (BDA) in the healthcare sector; describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data; examines real-time analytics solutions; introduces in-database processing and in-memory analytics techniques for data mining; discusses the use of mainframes for handling real-time big data and the latest types of data management systems for BDA; provides information on the use of cluster, grid and cloud computing systems for BDA; reviews the peer-to-peer techniques and tools and the common information visualization techniques, used in BDA.