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-contained Core Data Analysis: Summarization, Correlation and Visualization is aimed at those who are eager to participate in developing the field;
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topics including (but not limited to) spatial data visualization; biomedical visualization and applications; image/video summarization and;
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R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data;
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R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data;
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This book tackles important problems of anomaly detection and health status analysis in complex core router systems, integral to today's;
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This book tackles important problems of anomaly detection and health status analysis in complex core router systems, integral to today's;
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Visualization and analysis tools, techniques, and algorithms have undergone a rapid evolution in recent decades to accommodate explosive;
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robust statistical methods adapted for compositional data analysis, such as supervised and unsupervised methods like PCA, correlation analysis;
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solutions to problems related to dataframes, data manipulation summarization, and exploratory analysis. You will improve your skills in graph data;
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Data, and an Appendix on Data Summarization and Visualization * Offers extensive coverage of the R statistical programming language * Contains;
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fundamental characteristics and principles of language use and understanding. Automatic summarization is a desirable technique for processing big data;
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. You'll begin by installing Python 3, see how to work in Jupyter notebook, and explore Leather, Python's popular data visualization charting;
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begin by installing Python 3, see how to work in Jupyter notebook, and explore Leather, Pythons popular data visualization charting library;
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applications of robust correlation methods to exploratory data analysis, multivariate statistics, statistics of time series, and to real-life data;
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Data Analysis and Visualization in Genomics and Proteomics is the first book addressing integrative data analysis and visualization in this;
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Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific;
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Statistics and Data Visualization Using R: The Art and Practice of Data Analysis teaches students statistics visually, focusing on;
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methods for the analysis and visualization of scientific data. Theoretical concepts are presented in a painstaking but intuitive manner, with;
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methods for the analysis and visualization of scientific data. Theoretical concepts are presented in a painstaking but intuitive manner, with;
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Visualization and Verbalization of Data shows how correspondence analysis and related techniques enable the display of data in graphical;
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Data Analytics and Visualization in Quality Analysis using Tableau goes beyond the existing quality statistical analysis. It helps quality;
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security * Compare and master today's most useful tools for security visualization Contains the live CD Data Analysis and;
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If you are planning to create data analysis and visualization tools in the context of science, engineering, economics, or social science;
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This second and revised edition contains a detailed introduction to the key classes of intelligent data analysis methods. The twelve;
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capabilities and there are many new possibilities for data displays. This book gives an overview of modern data visualization methods, both in theory;
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for designing interactive visual data analysis solutions, discusses factors influencing the design, and examines the involved processes. The;
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for designing interactive visual data analysis solutions, discusses factors influencing the design, and examines the involved processes. The;
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