AIML Challenges: Difference between revisions
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This Dataset may be found at the [[Data:AI&ML_Challenge_Dataset|'''CSDMS Substrates Dataset page''']]. | This Dataset may be found at the [[Data:AI&ML_Challenge_Dataset|'''CSDMS Substrates Dataset page''']]. | ||
The Zipfile holds Documentation, Training Data and a Starter Python program. | The Zipfile holds Documentation, Training Data and a Starter Python program. The data come from the system 'dbSEABED' ([http://instaar.colorado.edu/~jenkinsc/dbseabed/ '''link''']). | ||
The data come from the system 'dbSEABED' ([http://instaar.colorado.edu/~jenkinsc/dbseabed/ '''link''']). | |||
Any questions: email Dr Chris Jenkins (chris.jenkins@colorado.edu) at INSTAAR, University of Colorado Boulder. | Any questions: email Dr Chris Jenkins (chris.jenkins@colorado.edu) at INSTAAR, University of Colorado Boulder. | ||
Revision as of 13:18, 16 August 2019
The Earth Surface Modeling AI&ML Training Data
The idea here is to serve datasets that can be used to compare the performance of different ML methods, such as Neural Networks, Random Forest and their variants for actual data. The data can also be used for education in the subject.
1. The Seabed Offshore of NE USA
This Dataset may be found at the CSDMS Substrates Dataset page. The Zipfile holds Documentation, Training Data and a Starter Python program. The data come from the system 'dbSEABED' (link).
Any questions: email Dr Chris Jenkins (chris.jenkins@colorado.edu) at INSTAAR, University of Colorado Boulder.
Example outputs of mapped Seabed Character
