“…In this paper we present an integration of hardware-accelerated workloads into the Grid through the declaration of dedicated queues with access to hardware accelerators and the use of linux container images holding a modern data science software stack. A frequent use-case of in the development of machine learning algorithms is the optimization of neural networks through the tuning of their hyper parameters. …”
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“…A solution to these challenges is presented, which allows training neural network classifiers using solutions from the Big Data and data science ecosystems, integrated with tools, software, and platforms common in the HEP environment. …”
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“…Unifying theories of information, optimization, and statistical physics, the value of information theory has gained recognition in data science, machine learning, and artificial intelligence. …”
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“…The book lies at the interface of mathematics, social media analysis, and data science. Its authors aim to introduce a new dynamic modeling approach to the use of partial differential equations for describing information diffusion over online social networks. …”
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“…The combination of data science, cloud deployment options and associated economics allows to burst out heterogeneously, exploring the full potential of cloud-based services.…”
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“…The open source and introductory HEP software curriculum and several software modules on techniques and methods for computing and data science have enabled users to jump start research and contributions to the field. …”
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“…Machine learning is quickly evolving and expanding, with recent great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, and modern machine learning approaches, especially deep learning,  are rapidly making their way into the analysis of High Energy Physics data to study more and more complex problems. …”
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“…That is a one-of-a-kind professional who works at the crossroads of clinical radiography, data science, and information technology. Imaging informaticians are becoming crucial players in expanding, assessing, and implementing AI in the medical setting. …”
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“…A well-trained midwife can prevent most of these maternal and newborn deaths. Data science models together with logs generated by users of online learning applications for midwives can help improve their learning competencies. …”
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“…Graph clustering is a fundamental problem in machine learning with numerous applications in data science. State-of-the-art approaches to the problem, Louvain and Leiden, aim at optimizing the modularity function. …”
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“…This re-implementation yields similar, but not identical, results: it achieves higher model likelihood, allows speed improvements on large datasets, as shown in experiments on TCGA data, and can be more easily interfaced with modern python-based data science tools. AVAILABILITY AND IMPLEMENTATION: PyDESeq2 is released as an open-source software under the MIT license. …”
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“…CONCLUSION: Only by sharing experiments, data, metadata, derived data and analysis workflows will neuroimaging establish itself as a true data science.…”
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“…Genomics is a Big Data science and is going to get much bigger, very soon, but it is not known whether the needs of genomics will exceed other Big Data domains. …”
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“…Outlier or anomaly detection in large data sets is a fundamental task in data science, with broad applications. However, in real data sets with high-dimensional space, most outliers are hidden in certain dimensional combinations and are relative to a user’s search space and interest. …”
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“…Emerging issues of team-based care, precision medicine, and big data science underscore the need for health information technology (HIT) tools for integrating complex data in consistent ways to achieve the triple aims of improving patient outcomes, patient experience, and cost reductions. …”
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“…From the perspective of a neurosurgeon – (app) developer it explains how technical progress has shaped the world's “most rated and highest rated” neurosurgical mobile application, with particular attention for operating system diversity on mobile hardware, cookbook medicine, regulatory affairs (in particular regarding software as a medical device), and new developments in the field of clinical data science, machine learning, and predictive analytics. …”
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“…Ethical issues involving data may be more challenging than the ethical challenges of some other advanced technologies partly because data and data science are ubiquitous, having the potential to impact all aspects of life, and partly because of their intrinsic complexity. …”
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“…In this paper, we present the concept of data nature and introduce the problems arising from data nature, and then we define a new discipline named dataology (also called data science or science of data), which is an umbrella of theories, methods and technologies for studying data nature. …”
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“…The data science and AI community has gathered around the world to support tackling the climate change problem in different domains. …”
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“…Our recommendations for improving software availability, usability, and archival stability aim to foster a sustainable data science ecosystem in life science research.…”
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