Veridical Data Science
10. prosince 2019
O prezentaci
Data science is a field of evidence-seeking that combines data with domain information to generate new knowledge. It addresses key considerations in AI regarding when and where data-driven solutions are reliable and appropriate. Such considerations require involvement from humans who collectively understand the domain and tools used to collect, process, and model data. Throughout the data science life cycle, these humans make judgment calls to extract information from data. Veridical data science seeks to ensure that this information is reliable, reproducible, and clearly communicated so that empirical evidence may be evaluated in the context of human decisions. Three core principles: predictability, computability, and stability (PCS) provide the foundation for veridical data science. In this talk we will present a unified PCS framework for data analysis, consisting of both a workflow and documentation, illustrated through iterative random forests and case studies from genomics and precision medicine.Data science is a field of evidence-seeking that combines data with domain information to generate new knowledge. It addresses key considerations in AI regarding when and where data-driven solutions are reliable and appropriate. Such considerations require involvement from humans who collectively understand the domain and tools used to collect, process, and model data. Throughout the data science life cycle, these humans make judgment calls to extract information from data. Veridical data scienc…
Kategorie
Umělá inteligence a data science
Kategorie · 10,8k prezentací
O organizátorovi (NIPS 2019)
Neural Information Processing Systems (NeurIPS) is a multi-track machine learning and computational neuroscience conference that includes invited talks, demonstrations, symposia and oral and poster presentations of refereed papers. Following the conference, there are workshops which provide a less formal setting.
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Sdílení
Doporučená videa
Prezentace na podobné téma, kategorii nebo přednášejícího
WiML D&I Chairs Remarks
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Contributed Talk Track 3 - Learning Fair Classifiers in Online Stochastic Setting
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Opening Remarks
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Invited talk: Finding the right Balance of Modelling and Learning for Vision-based Robot Manipulation
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The Differentiable Curry
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