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Sensotrendin esitys ensimmäistä kertaa järjestetyillä Diabetesmessuilla. Itse kalvot ovat lähinnä kuvia, mutta muistiinpanoista näkyy myös tarinaa (helpompi seurata, jos lataat PowerPoint-tiedoston).
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Intervieuw kappersnieuws zf
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Corte bb
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diegofriolin
Fotografies
Fotografies
perletaful
Sensotrendin esitys ensimmäistä kertaa järjestetyillä Diabetesmessuilla. Itse kalvot ovat lähinnä kuvia, mutta muistiinpanoista näkyy myös tarinaa (helpompi seurata, jos lataat PowerPoint-tiedoston).
Sensotrend Diabetesmessuilla
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Mikael Rinnetmäki
Días de la semana, meses del año y estaciones
La semana
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aprendiendototeach
666_zornola(justin bieber).doc
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ElhuyarOlinpiada
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Trabalho da disciplina de Novas Tecnologias - 08 de Agosto de 2013. Faculdade Porto. Porto Velho - Rondônia
Trabalho POS - FIP 2013
Trabalho POS - FIP 2013
Creative S.I
20160731131055894
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Mohamad Almousa
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rhsmediastudies
Para nosotros que son los derechos humanos.
¿Qué son los derechos humanos?
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Madali12345
Resume - Ganesh Ramakrishnan
Resume - Ganesh Ramakrishnan
Ramakrishnan Ganesh
Geographically Weighted Regression (GWR) is a local version of spatial regression that captures spatial dependency in regression analysis. GWR has many application in practice as a visualization and prediction tool for spatial exploration- (e.g in climate, economy, medical). However, this locally regression model is slow in process upon the volume of calculations and the spatial getting bigger. Improving performance of GWR is an critical issue, but their distributed implementations have not been studied. Recently, with the advent of Spark as well MapReduce framework, the development of machine learning applications and parallel programming becomes easier. In this article, we propose several large-scale implementations of distributed GWR, leveraging Spark framework. We implemented and evaluated these approaches with large datasets. To our best knowledge, this is the first work addressing GWR at large-scale.
Large-Scale Geographically Weighted Regression on Spark
Large-Scale Geographically Weighted Regression on Spark
Viet-Trung TRAN
License keys 2012115
License keys 2012115
prasadmvreddy
Serial number
Serial number
Andi Syahputra Baru
Serial numbers
Serial numbers
Anneth Bun-as
1 million serial numbers of different softwares
1 million serial numbers of different softwares
mifdov
Contenu connexe
En vedette
Trabalho da disciplina de Novas Tecnologias - 08 de Agosto de 2013. Faculdade Porto. Porto Velho - Rondônia
Trabalho POS - FIP 2013
Trabalho POS - FIP 2013
Creative S.I
20160731131055894
20160731131055894
Mohamad Almousa
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Official Productions - Storyboard
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rhsmediastudies
Para nosotros que son los derechos humanos.
¿Qué son los derechos humanos?
¿Qué son los derechos humanos?
Madali12345
Resume - Ganesh Ramakrishnan
Resume - Ganesh Ramakrishnan
Ramakrishnan Ganesh
Geographically Weighted Regression (GWR) is a local version of spatial regression that captures spatial dependency in regression analysis. GWR has many application in practice as a visualization and prediction tool for spatial exploration- (e.g in climate, economy, medical). However, this locally regression model is slow in process upon the volume of calculations and the spatial getting bigger. Improving performance of GWR is an critical issue, but their distributed implementations have not been studied. Recently, with the advent of Spark as well MapReduce framework, the development of machine learning applications and parallel programming becomes easier. In this article, we propose several large-scale implementations of distributed GWR, leveraging Spark framework. We implemented and evaluated these approaches with large datasets. To our best knowledge, this is the first work addressing GWR at large-scale.
Large-Scale Geographically Weighted Regression on Spark
Large-Scale Geographically Weighted Regression on Spark
Viet-Trung TRAN
License keys 2012115
License keys 2012115
prasadmvreddy
Serial number
Serial number
Andi Syahputra Baru
Serial numbers
Serial numbers
Anneth Bun-as
1 million serial numbers of different softwares
1 million serial numbers of different softwares
mifdov
En vedette
(10)
Trabalho POS - FIP 2013
Trabalho POS - FIP 2013
20160731131055894
20160731131055894
Official Productions - Storyboard
Official Productions - Storyboard
¿Qué son los derechos humanos?
¿Qué son los derechos humanos?
Resume - Ganesh Ramakrishnan
Resume - Ganesh Ramakrishnan
Large-Scale Geographically Weighted Regression on Spark
Large-Scale Geographically Weighted Regression on Spark
License keys 2012115
License keys 2012115
Serial number
Serial number
Serial numbers
Serial numbers
1 million serial numbers of different softwares
1 million serial numbers of different softwares
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Trame Musicale Georghe Zamfir The
Beauty and the Beast (La belle et la bête)
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