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OpendTect Webinar: How to prepare well logs to get optimal Machine Learning results
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This is a recording of the OpendTect Webinar: How to prepare well logs to get optimal Machine Learning results by FORCE 2020 Machine Learning winner Olawale Ibrahim for dGB Earth Sciences.
Getting the best set of training data (wells and logs) is essential for getting best lithology prediction results from Machine Learning models. With database access to a large number of available wells for doing this in OpendTect, manually visualizing and exploring this big data set of wells could be time consuming and also lead to less optimal performance. In this webinar, we show methods to extract the best set of training well data while also getting optimal prediction performance.
Keywords: Python, keras, bokeh, scikit, pandas, numpy, odpy, dgbpy, xgboost, rmse, Root Mean Squared Error, jupyter-notebook
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