Deep Learning/Machine Learning Technical Interest Group (TIG)

Applying new analytics, neural networks, computational approaches using structured and unstructured data, and also training neural networks with supervised and unsupervised algorithms. Chaired by Patrick Ng and Andrew Munoz.
Deep Learning - Machine Learning TIG
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0 Replies and 365 Views Read This First!      365  0 Started by  Bogdan Michka Welcome to AAPG N.E.T., an online space where you can Network, Engage and Talk. Please complete the following steps before you begin interacting with the discussion boards: 1. Take time to review your profile and privacy settings, paying attention to your display name and photo, as they will be used to identify your posts. 2. Read the Discussion Boards FAQ page to learn the rules and get familiar with the features: — pa...
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09 May 2017 03:37 PM
0 Replies and 17 Views AI surprised Google developers - tacking like human  17  0 Started by  Patrick Ng Note - encoding (chaining of alpha-numeric) , e.g., 'Be5' to move a bishop, makes powerful feature engineering when training machine to play chess.
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23 Feb 2021 10:12 PM
0 Replies and 28 Views How well do ML models generalize?  28  0 Started by  Patrick Ng One word - underspecification. Perspective - draw analogy between geophysical data processing (wiener-levinson,, homomorphic and minimum-entropy deconvolution) and ML models (logistic regression, neural network, LSTM, GAN), their ability to generalize d...
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18 Feb 2021 01:39 PM
0 Replies and 24 Views Texas Freeze Out cannot stop Energy in Data  24  0 Started by  Patrick Ng Update - as we tally up the Texas and Oklahoma freeze out, and recognize challenges many of our members face in the aftermath, not to mention pipes bursts, water damages etc, the three societies will postpone the EiD 2021 kick off to a later date (tentatively slated for April). There is time for us to better prepare and engage a larger audience. Additional considerations will be given to broaden geographic reach, and highlight the contributions AI and machine learning make. Meanwhile, all ...
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17 Feb 2021 09:17 PM
0 Replies and 38 Views Why Energy in Data 2021?  38  0 Started by  Patrick Ng As any emerging technologies, often we struggle through the initial period of cutting-edge and bleeding edge, before reaching wider adoption and wiser application. As in AVO (used to derisk prospects predrill) and depth imaging (credited for opening up the entire Gulf of Mexico deepwater subsalt play), “conventional wisdom” changed from convention to convention before we as an industry converged on a set of best practice based on play and geology. Anticipate the use of AI and machine lear...
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12 Feb 2021 12:57 PM
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