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1 Replies and 296 Views
Common Framework - Machine Learning and Geoscience 296 1
Started by Patrick Ng
During recent events, machine-learning focused Hackathon and Workshop, on July 19 and 26 respectively, it becomes apparent a common framework making ML relevant to geoscience will be very useful. Here a first-iteration tabulated template* is intended for further discussion. 1) Data Prep and Processing - AVO - say a simple two-term reflection amplitudes, R(𝜭) = P G * sin2(𝜭), AVZ(𝜙) = AVO vs azimuth, where 𝜭 denotes angle of reflection (in sub...
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0 Replies and 342 Views
Reinforcement Learning 342 0
Started by Patrick Ng
Recently I was asked 'is there benefit of reprocessing data and machine learning together' Yes. It has been standard business practice that every few years, with improved algorithm, we reprocess data, get higher resolution and a more detailed look. Like going from 4K to 8K HDTV, instead of 80 to 100 feet resolution in seismic, we may get that down to 40 ft. With higher resolution data, we’d retrain machine learning and get better results. Both go hand in hand. That brings up a good point....
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27 Sep 2018 11:53 AM |
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0 Replies and 290 Views
Neural Network to predict aftershocks in earthquakes 290 0
Started by Patrick Ng
The physics is relating transfer of stresses via elasticity (physical rock property). Instead of treating neural network output weights out of a 'black box', according to the authors, 'We could look at what was coming out of this network and actually make sense of it, and it’s actually pointed us to some possibly different physical theories of what causes earthquake triggering, and so it’s leading us in a new direction, which is exciting for us.” For the full story, click on link below. Li...
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30 Aug 2018 01:10 PM |
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1 Replies and 336 Views
Azure, AWS or GCP - Q2 Snapshot 336 1
Started by Patrick Ng
As in machine learning, lets define Geek meter 1-10 (max out , 10 all command lines, scripts, bash etc.;1 - drag-n-drop with minimal coding). Here is a snapshot from the perspective of a practitioner with deployment as the goal. If much time-resource is spent on collaboration, workflow design and enrollment of practitioners from different disciplines, Azure machine learning (ML) Studio is a natural fit with data processing hand in glove. Highly intuitive. Low on the Geek meter. ...
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0 Replies and 373 Views
Students beat Google's Machine Learning Code 373 0
Started by Patrick Ng
Machine learning is not just an algorithm thing. It is a process. https://fossbytes.com/googles-machine-learning-code-beaten-by-student-coders/utm_medium=browser-notification&utm_source=onesignal&utm_campaign=notification-engagement Common framework analogy - data prep and wrangling are critical to machine learning success, as near-surface statics in land seismic data processing. No matter how sophisticated the imaging and inversion algorithms deployed, they cannot fix what is not taken c...
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14 Aug 2018 03:07 PM |
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