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of applying visualization and visual analytic techniques to large-scale applications. Topics of interest include: programming tools; methodologies for;
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MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance;
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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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MATLAB, a software package for high-performance numerical computation and visualization, is one of the most widely used tools in the;
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Here is an ideal textbook on software visualization, written especially for students and teachers in computer science. It provides a broad;
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An Updated Guide to the Visualization of Data for Designers, Users, and Researchers Interactive Data Visualization: Foundations;
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An Updated Guide to the Visualization of Data for Designers, Users, and Researchers Interactive Data Visualization: Foundations;
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how Pharo leverages visualization development against traditional frameworks and toolkits. Agile Visualization with Pharo focuses on the;
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tools to accomplish this is Interactive Data Language (IDL), a programming and visualization environment that facilitates numerical modeling;
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the broadest applicability across fields, the second edition of Data Visualization: Principles and Practice provides a streamlined;
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with the broadest applicability across fields, the second edition of Data Visualization: Principles and Practice provides a streamlined;
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-face and virtual reach high performance in today's work environment. As teams become more and more global and distributed, visualization;
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This book features chapters which explore algorithms, programming languages, systems, tools and theoretical models aimed at high;
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visualization but you don't know where to start, then this book will guide you from the start and help you understand data, data formats, data;
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, full coverage is given to scientific visualization and to the architectures (scientific workstations and vector and parallel supercomputers;
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approach using libraries such as leather, NumPy, Matplotlib, and Pandas will serve as a template for business and scientific visualizations;
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approach using libraries such as leather, NumPy, Matplotlib, and Pandas will serve as a template for business and scientific visualizations. YoĆ¼ll;
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Wring more out of the data with a scientific approach to analysis Graph Analysis and Visualization brings graph theory out of the lab and;
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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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, without knowing how to optimize program performance and without understanding how programs interact with the larger computer system;
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The book discusses the fundamentals of high-performance computing. The authors combine visualization, comprehensibility, and strictness;
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The book discusses the fundamentals of high-performance computing. The authors combine visualization, comprehensibility, and strictness;
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environment. From the fundamentals of system performance to using analysis and optimization tools to their fullest, this wide-ranging resource shows;
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Build efficient and fast Qt applications, target performance problems, and discover solutions to refine your code Key Features Build;
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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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, implement the visualization of results, and design the GUI. This text teaches the core concepts of computer programming arrays, loops, functions;
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