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    <title>Forecasting on DASYA</title>
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    <description>Recent content in Forecasting on DASYA</description>
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    <copyright>© DASYA, IT University of Copenhagen</copyright>
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      <title>Evaluating AutoML for Forecasting Domestic Electricity Data</title>
      <link>https://dasya.itu.dk/for-students/proposals/archive/automl-forecasting-energy/</link>
      <pubDate>Thu, 20 Aug 2020 00:00:00 +0000</pubDate>
      
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      <description>With the recent hunger for being &amp;ldquo;data driven&amp;rdquo;, many organizations are eager for integrating ML in there decision making process. Unfortunately, competent data scientists are still relatively scarce, and manual model development cannot keep up with the demand for magic AI solutions. This is no less true when it comes to forecasting. Knowing the future is extremely handy when making decisions.
AutoML for Time Series Forecasting Subsequently many systems are now developing and integrating AutoML tools for time series forecasting.</description>
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      <title>Wind turbine electricity production prediction</title>
      <link>https://dasya.itu.dk/for-students/proposals/archive/wind-turbine-electricity-production-prediction/</link>
      <pubDate>Mon, 16 Dec 2019 00:00:00 +0000</pubDate>
      
      <guid>https://dasya.itu.dk/for-students/proposals/archive/wind-turbine-electricity-production-prediction/</guid>
      <description>The goal of the project is to explore the accuracy of electricity production predictions based on historical data and weather predictions. This may be tackled as a sequence prediction problem using recurrent neural networks The long term goal is to incorporate wind turbines in the reserve market for electricity.</description>
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      <title>Powering the Orkney Cloud</title>
      <link>https://dasya.itu.dk/for-students/projects/archive/powering-the-orkney-cloud/</link>
      <pubDate>Thu, 31 May 2018 00:00:00 +0000</pubDate>
      
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      <description>Modeling and Understanding Curtailment in Orkney</description>
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