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visualization of time-oriented data. Separate chapters discuss interaction techniques and computational methods for supporting the visual data analysis;
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visualization of time-oriented data. Separate chapters discuss interaction techniques and computational methods for supporting the visual data analysis;
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visualization of time-oriented data along three key questions: what is being visualized (data), why something is visualized (user tasks), and how it;
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barriers impeding information management at the point-of-care and discusses strategies for better data visualization including multimedia displays;
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of computer graphics with a practitioner-oriented review of the latest 3-D graphics display and visualization techniques. Each chapter is written by;
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of computer graphics with a practitioner-oriented review of the latest 3-D graphics display and visualization techniques. Each chapter is written by;
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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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-oriented data This popular book continues to explore the fundamental components of the visualization process, from the data to the human viewer;
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techniques for time-oriented data This popular book continues to explore the fundamental components of the visualization process, from;
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Exploit the visualization capabilities of Kibana and build powerful interactive dashboards About This Book * Introduction to data;
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For some time, medicine has been an important driver for the development of data processing and visualization techniques. Improved;
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, and so on. We focus on the most popular libraries to execute the tasks of big data visualization and explore big data oriented tools such as;
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statistics you see on your favorite news sites, the art of data graphics or visualization is fast becoming a movement of its own. In Data Points;
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Prevalent types of data in scientific visualization are volumetric data, vector field data, and particle-based data. Particle data;
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, allowing direct visualization and interaction of multi-dimensional data. As the amount of data is steadily increasing, memory and bandwidth;
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This book presents the fundamentals and advances in the field of data visualization and knowledge engineering, supported by case studies;
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, and respond to emerging threats and vulnerabilities. Security Data Visualization is a well-researched and richly illustrated introduction to;
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tutorials. It begins with a description of the huge growth of data and visualization in industry, news, and gov't and opportunities for those who;
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Quickly start programming with Python 3 for data visualization with this step-by-step, detailed guide. This book's programming-friendly;
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Quickly start programming with Python 3 for data visualization with this step-by-step, detailed guide. This books programming-friendly;
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Create your own clear and impactful interactive data visualizations with the powerful data visualization libraries of Python Key Features;
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adopted in Cybersecurity-oriented frameworks. The recent advent of Big Data paradigms and the use of data science methods, has resulted in a;
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in creating impressive data visualization tools using modern graphics hardware. Whether you are a developer, engineer, or scientist, if you are;
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A swift and practical introduction to building interactive data visualization apps in Python, known as dashboards. You've seen dashboards;
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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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Data Visualization Made Simple is a practical guide to the fundamentals, strategies, and real-world cases for data visualization, an;
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