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A case study of the research, design, implementation and commercial distribution of PACE, a decision support system, is provided by this work. The... Læs mere
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Covers the field of computing, from its technological status through its social, economic and political significance. This book contains more than 30... Læs mere
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This book treats, in five sections, the existing and future surveys, their digitization and their impact on astronomy. It is designed to serve as a reference for people in the field and for those who wish to engage in using or producing sky surveys.
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Storing, managing and giving access to data collected by astronomical observatories is a challenge of modern astronomy. This book presents a selection of... Læs mere
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This volume aims to present recent advances in database technology from the viewpoint of the novel database paradigms proposed in the last decade. It focuses on the... Læs mere
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Discussing some key scientific and technological developments in high performance computing, identifying significant trends, and defining desirable research objectives, this text covers general concepts and emerging systems, software technology, algorithms and applications.
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Generative Adversarial Networks (GANs) in Practice is an all-inclusive resource that provides a solid foundation on GAN methodologies, their application to real-world projects, and their underlying mathematical and theoretical concepts.
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The release of ChatGPT has kicked off an arms race in Machine Learning (ML), however ML has also been described as a black box and very hard to understand. This book eases you... Læs mere
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Test-driven data analysis is the synthesis of ideas from test-driven development of software to data-intensive work including data science, data analysis, and data engineering. It is a methodology for improving the quality of data and of analytical pipelines and processes.
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This book offers a comprehensive discussion of the growing importance of ethical considerations in algorithmic systems to introduce practical frameworks and tools for identifying ethical risks, ensuring fair outcomes, and maintaining transparency in algorithmic processes.