doi.org/10.5281/zenodo.7740850

Preview meta tags from the doi.org website.

Linked Hostnames

14

Search Engine Appearance

Google

https://doi.org/10.5281/zenodo.7740850

Non-Sequential Machine Learning Pipelines with pyWATTS

pyWATTS is an open-source Python-based workflow automation tool for time series analysis. pyWATTS simplifies the evaluation process and the design of repetitive machine learning experiments with time series by providing a powerful pipeline solution including preprocessing and analysis modules. Unlike existing sequential pipeline solutions, pyWATTS enables more complex and non-sequential pipelines. Such non-sequential pipelines are beneficial, for example, in forecasting electrical load time series, detecting anomalies in time series, or generating synthetic time series. This talk presents the basic ideas of pyWATTS, the current features, and existing use cases. It also gives an outlook on the future developments of pyWATTS and the cooperation with sktime.



Bing

Non-Sequential Machine Learning Pipelines with pyWATTS

https://doi.org/10.5281/zenodo.7740850

pyWATTS is an open-source Python-based workflow automation tool for time series analysis. pyWATTS simplifies the evaluation process and the design of repetitive machine learning experiments with time series by providing a powerful pipeline solution including preprocessing and analysis modules. Unlike existing sequential pipeline solutions, pyWATTS enables more complex and non-sequential pipelines. Such non-sequential pipelines are beneficial, for example, in forecasting electrical load time series, detecting anomalies in time series, or generating synthetic time series. This talk presents the basic ideas of pyWATTS, the current features, and existing use cases. It also gives an outlook on the future developments of pyWATTS and the cooperation with sktime.



DuckDuckGo

https://doi.org/10.5281/zenodo.7740850

Non-Sequential Machine Learning Pipelines with pyWATTS

pyWATTS is an open-source Python-based workflow automation tool for time series analysis. pyWATTS simplifies the evaluation process and the design of repetitive machine learning experiments with time series by providing a powerful pipeline solution including preprocessing and analysis modules. Unlike existing sequential pipeline solutions, pyWATTS enables more complex and non-sequential pipelines. Such non-sequential pipelines are beneficial, for example, in forecasting electrical load time series, detecting anomalies in time series, or generating synthetic time series. This talk presents the basic ideas of pyWATTS, the current features, and existing use cases. It also gives an outlook on the future developments of pyWATTS and the cooperation with sktime.

  • General Meta Tags

    22
    • title
      Non-Sequential Machine Learning Pipelines with pyWATTS
    • charset
      utf-8
    • X-UA-Compatible
      IE=edge
    • viewport
      width=device-width, initial-scale=1
    • google-site-verification
      5fPGCLllnWrvFxH9QWI0l1TadV7byeEvfPcyK2VkS_s
  • Open Graph Meta Tags

    4
    • og:title
      Non-Sequential Machine Learning Pipelines with pyWATTS
    • og:description
      pyWATTS is an open-source Python-based workflow automation tool for time series analysis. pyWATTS simplifies the evaluation process and the design of repetitive machine learning experiments with time series by providing a powerful pipeline solution including preprocessing and analysis modules. Unlike existing sequential pipeline solutions, pyWATTS enables more complex and non-sequential pipelines. Such non-sequential pipelines are beneficial, for example, in forecasting electrical load time series, detecting anomalies in time series, or generating synthetic time series. This talk presents the basic ideas of pyWATTS, the current features, and existing use cases. It also gives an outlook on the future developments of pyWATTS and the cooperation with sktime.
    • og:url
      https://zenodo.org/records/7740850
    • og:site_name
      Zenodo
  • Twitter Meta Tags

    4
    • twitter:card
      summary
    • twitter:site
      @zenodo_org
    • twitter:title
      Non-Sequential Machine Learning Pipelines with pyWATTS
    • twitter:description
      pyWATTS is an open-source Python-based workflow automation tool for time series analysis. pyWATTS simplifies the evaluation process and the design of repetitive machine learning experiments with time series by providing a powerful pipeline solution including preprocessing and analysis modules. Unlike existing sequential pipeline solutions, pyWATTS enables more complex and non-sequential pipelines. Such non-sequential pipelines are beneficial, for example, in forecasting electrical load time series, detecting anomalies in time series, or generating synthetic time series. This talk presents the basic ideas of pyWATTS, the current features, and existing use cases. It also gives an outlook on the future developments of pyWATTS and the cooperation with sktime.
  • Link Tags

    9
    • alternate
      https://zenodo.org/records/7740850/files/pyWATTS@deRSE23_final.pdf
    • apple-touch-icon
      /static/apple-touch-icon-120.png
    • apple-touch-icon
      /static/apple-touch-icon-152.png
    • apple-touch-icon
      /static/apple-touch-icon-167.png
    • apple-touch-icon
      /static/apple-touch-icon-180.png

Links

47