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Predicting Spatial Data with Rotation Gradients and Machine Learning

De Pinho, Bruno


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  <dc:creator>De Pinho, Bruno</dc:creator>
  <dc:date>2017-09-12</dc:date>
  <dc:description>Using Machine Learning (ML) algorithms to predict Airbourne Geophysics. A simple, but powerful solution using Rotation Gradients to add complexity to the model with a Automated Machine Learning (AutoML) implementation.</dc:description>
  <dc:identifier>https://zenodo.org/record/889923</dc:identifier>
  <dc:identifier>10.5281/zenodo.889923</dc:identifier>
  <dc:identifier>oai:zenodo.org:889923</dc:identifier>
  <dc:relation>doi:10.5281/zenodo.889922</dc:relation>
  <dc:rights>info:eu-repo/semantics/restrictedAccess</dc:rights>
  <dc:subject>machine-learning, geophysics, geology, python, automl</dc:subject>
  <dc:title>Predicting Spatial Data with Rotation Gradients and Machine Learning</dc:title>
  <dc:type>info:eu-repo/semantics/lecture</dc:type>
  <dc:type>lesson</dc:type>
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