Results 31 to 40 of about 28,511,988 (353)
Journal of the Medical Library Association, 2020 Increasingly, users of health and biomedical libraries need assistance with challenges they face in working with their own and others’ data. Librarians have a unique opportunity to provide valuable support and assistance in data science and open science ...
Lisa Federer +5 more
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Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence [PDF]
Inf., 2020 Smarter applications are making better use of the insights gleaned from data, having an impact on every industry and research discipline. At the core of this revolution lies the tools and the methods that are driving it, from processing the massive piles
S. Raschka +2 more
semanticscholar +1 more source
The Art and Practice of Data Science Pipelines: A Comprehensive Study of Data Science Pipelines In Theory, In-The-Small, and In-The-Large [PDF]
International Conference on Software Engineering, 2021 Increasingly larger number of software systems today are including data science components for descriptive, predictive, and prescriptive analytics. The collection of data science stages from acquisition, to cleaning/curation, to modeling, and so on are ...
Sumon Biswas +2 more
semanticscholar +1 more source
Spectral Methods for Data Science: A Statistical Perspective [PDF]
Found. Trends Mach. Learn., 2020 Spectral methods have emerged as a simple yet surprisingly effective approach for extracting information from massive, noisy and incomplete data. In a nutshell, spectral methods refer to a collection of algorithms built upon the eigenvalues (resp ...
Yuxin Chen +3 more
semanticscholar +1 more source
Security of Data Science and Data Science for Security [PDF]
, 2019 In this chapter, we present a brief overview of important topics regarding the connection of data science and security. In the first part, we focus on the security of data science and discuss a selection of security aspects that data scientists should consider to make their services and products more secure.
Tellenbach, Bernhard +2 more
openaire +3 more sources
Data Science and Earth System Science
, 2022 AbstractData-driven science has turned into a fourth fundamental paradigm of performing research. Earth System Science, following a holistic approach in unraveling the complex network of processes and interactions shaping system Earth, particularly profits from embracing data-driven approaches next to observation and modeling.
zu Castell, Wolfgang +8 more
openaire +4 more sources
IEEE Computer Graphics and Applications, 2017 Data science methods and approaches address all stages of transition from data to knowledge and action. Visualization of this data is essential for human understanding of the subject under study, analytical reasoning about it, and generating new knowledge.
Andrienko, Gennady +2 more
openaire +2 more sources
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning [PDF]
Chemical Reviews, 2020 By combining metal nodes with organic linkers we can potentially synthesize millions of possible metal–organic frameworks (MOFs). The fact that we have so many materials opens many exciting avenues but also create new challenges.
K. Jablonka +3 more
semanticscholar +1 more source
Research Ideas and Outcomes, 2017 A proposal to create a full-semester zero-entry level course about the responsible handling of research data and the associated analyses, storage, and sharing.
Nicolas Schmelling
doaj +2 more sources
In the Backrooms of Data Science
Journal of the AIS, 2022 Much information systems research on data science treats data as preexisting objects and focuses on how these objects are analyzed. Such a view, however, overlooks the work involved in finding and preparing the data in the first place, such that they are
Elena Parmiggiani +2 more
semanticscholar +1 more source