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developers who are interested in visualization techniques for large, dynamic particle-based data. Its explanations focus on GPU-accelerated;
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introduces pixel-exact evaluation of higher-order solution data on the GPU, which demonstrates the importance of per-pixel rendering versus linear;
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The utilization of modern graphics hardware (GPU) for visualization and computation purposes, has become highly relevant in recent years;
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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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, fluid mechanics, nano-materials, data-mining , earthquakes ,mantle convection, visualization. It will show the public why GPU computing;
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, fluid mechanics, nano-materials, data-mining , earthquakes ,mantle convection, visualization. It will show the public why GPU computing;
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Interactive display and visualization of large geometric and textured models is becoming a fundamental capability. There are numerous;
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reader is made familiar with the basics of visual encoding and gets to know numerous visualization techniques for multivariate data, temporal;
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reader is made familiar with the basics of visual encoding and gets to know numerous visualization techniques for multivariate data, temporal;
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Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. Key Features Leverage the Jupyter Notebook for;
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The richly illustrated Interactive Web-Based Data Visualization with R, plotly, and shiny focuses on the process of programming interactive;
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The richly illustrated Interactive Web-Based Data Visualization with R, plotly, and shiny focuses on the process of programming interactive;
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you're ready to create your own web-based data visualizations-and know either Python or JavaScript- this is the book for you. Learn how to;
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-point format, parallel patterns, and dynamic parallelism are covered in depth. This best-selling guide to CUDA and GPU parallel programming has;
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Data Mining and Data Visualization focuses on dealing with large-scale data, a field commonly referred to as data mining. The book;
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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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develop a wide range of impressive OpenGL-based applications for your unique data visualization needs, on platforms ranging from conventional;
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) Interactive & Digital Media. The book also addresses the fundamental issues in GPU computing with a focus on big data processing. Researchers and;
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Nsight Effectively use CUDA libraries such as cuBLAS, cuFFT, and cuSolver Apply GPU programming to modern data science applications Book;
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and Visualization), course: Seminar Computer Vision, language: English, abstract: Visualization of large data sets, especially the;
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this beginner-friendly workshop Key Features Discover the essential tools and methods of data visualization Learn to use standard;
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stunning SVG and Canvas-based data visualizations while writing testable, extensible code,as accurate and informative as it is visually stimulating;
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that empowers users to create scalable, data-driven graphics ranging from simple charts to fantastic interactive visualizations. Based on the;
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: Presents tips & tricks on real-time rendering of special effects and visualization data on common consumer software platforms such as PCs, video;
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: Presents tips & tricks on real-time rendering of special effects and visualization data on common consumer software platforms such as PCs, video;
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data visualizations. Based entirely on open web standards, D3 provides an integrated collection of tools for efficiently binding data to;
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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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Einde inhoud
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