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Ergebnis der Suche nach: "Machine Learning"
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Artikel 17881 What do we want to know about MOOCs? Results from a machine learning approach to a systematic literature mapping review
Enthalten in International journal of educational technology in higher education Bd. 19, 14.10.2022, Nr. 1, date:12.2022: 1-22
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Artikel 17882 What factors preventing the older adults in China from living longer: a machine learning study
Enthalten in BMC geriatrics Bd. 24, 22.7.2024, Nr. 1, date:12.2024: 1-11
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Artikel 17883 WHAT IDENTIFIES A WHALE BY ITS FLUKE? ON THE BENEFIT OF INTERPRETABLE MACHINE LEARNING FOR WHALE IDENTIFICATION
Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. V-2-2020, 2020: 1005-1012
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Artikel 17884 What is the impact of national public expenditure and its allocation on neonatal and child mortality? A machine learning analysis
Enthalten in BMC public health Bd. 23, 28.4.2023, Nr. 1, date:12.2023: 1-11
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Artikel 17885 What we can do with one qubit in quantum machine learning: ten classical machine learning problems that can be solved with a single qubit
Enthalten in Quantum machine intelligence Bd. 6, 12.11.2024, Nr. 2, date:12.2024: 1-24
Online Ressource
Artikel 17886 When are they coming? Understanding and forecasting the timeline of arrivals at the FC Barcelona stadium on match days
Enthalten in Machine learning Bd. 113, 26.3.2024, Nr. 5, date:5.2024: 2765-2794
Online Ressource
Artikel 17887 When machine learning and neural networks marry real-time scheduling
Enthalten in Real-time systems Bd. 61, 7.7.2025, Nr. 2, date:6.2025: 320-325
Online Ressource
Artikel 17888 When not to use machine learning: A perspective on potential and limitations
Enthalten in Materials Research Society: MRS bulletin Bd. 47, 21.10.2022, Nr. 9, date:9.2022: 968-974
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Artikel 17889 When physics meets machine learning: a survey of physics-informed machine learning
Enthalten in Machine learning for computational science and engineering Bd. 1, 7.5.2025, Nr. 1, date:6.2025: 1-23
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Artikel 17890 When the crowd gets it wrong – the limits of collective wisdom in machine learning
Enthalten in Scientific reports Bd. 15, 1.7.2025, Nr. 1, date:12.2025: 1-11
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