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Data Analysis for Omic Sciences: Methods and Applications, Volume 82, shows how these types of challenging datasets can be analyzed;
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Learn exploratory data analysis concepts using powerful R packages to enhance your R data analysis skills Key Features Speed up your;
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Intelligent Data Analysis for Biomedical Applications: Challenges and Solutions presents specialized statistical, pattern recognition;
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Covering the general process of data analysis to finding, collecting, organizing, and presenting data, this book offers a complete;
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Covering the general process of data analysis to finding, collecting, organizing, and presenting data, this book offers a complete;
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This book focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data;
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Critical Theory and Qualitative Data Analysis in Education offers a path-breaking explanation of how critical theories can be used within;
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For graduate-level courses in Marketing Research, Research Design and Data Analysis. Multivariate Data Analysis provides an applications;
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For graduate-level courses in Marketing Research, Research Design and Data Analysis. Multivariate Data Analysis provides an applications;
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For graduate-level courses in Marketing Research, Research Design and Data Analysis. Multivariate Data Analysis provides an applications;
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Data Analysis, Learning Symbolic & Numeric Knowledge Proceedings Of The Conference On Data Analysis, Learning Symbolic & Numeric Knowledge;
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Fundamentals of Big Data Network Analysis for Research and Industry Hyunjoung Lee, Institute of Green Technology, Yonsei University;
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This book presents emerging concepts in data mining, big data analysis, communication, and networking technologies, and discusses the state;
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Guides readers through the quantitative data analysis process including contextualizing data within a research situation, connecting data;
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Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become mainstream;
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Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become mainstream;
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practically and theoretically important areas of 'productivity analysisdata envelopment analysis' and 'data science/big data'. Data science;
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Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital;
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component. The topics addressed are from the following fields: Statistics and Data Analysis; Machine Learning and Knowledge Discovery; Data Analysis;
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Praise for the First Edition ...a well-written book on data analysis and data mining that provides an excellent foundation...CHOICE This;
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Get started using Python in data analysis with this compact practical guide. This book includes three exercises and a case study on getting;
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Get to grips with pandas-a versatile and high-performance Python library for data manipulation, analysis, and discovery About This Book;
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significant extension to the robust OLAP functionality of SQL 7.0 and provide a complete, end-to-end platform for analysis. Features include: data;
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This book offers an overview of traditional big visual data analysis approaches and provides state-of-the-art solutions for several scene;
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This volume gathers peer-reviewed contributions on data analysis, classification and related areas presented at the 28th Conference of the;
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Analysis provides an overview of many key statistical methods that have been developed in response to such new data streams and the associated;
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Analysis provides an overview of many key statistical methods that have been developed in response to such new data streams and the associated;
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