Working with time series : denoising and imputation frameworks to improve data density

Working with time series denoising and imputation frameworks to improve data density

"Anjali Samani (CircleUp) explains two simple frameworks for evaluating a dataset's candidacy for smoothing and quantitatively determining the optimal imputation strategy and the number of consecutive missing values that can be imputed without material degradation in signal quality. To ext...

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Detalles Bibliográficos
Otros Autores: Samani, Anjali, on-screen presenter (onscreen presenter)
Formato: Vídeo online
Idioma:Inglés
Publicado: [Place of publication not identified] : O'Reilly Media 2019.
Materias:
O'Reilly Strata Data Conference > (2019 : > New York, New York)
Time-series analysis > Data processing.
Machine learning.
Artificial intelligence.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009820450206719

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