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24 Apr 2019 07:43 AM |
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0 Replies and 614 Views
Resources - Machine Learning with Susan Nash 614 0
Started by Bogdan Michka
Watch Introduction to Machine Learning/Deep Learning with Susan Nash, AAPG's Director of Innovation & Emerging Science/Technology, AAPG Energy Insights Podcast Episode 7. https://www.aapg.org/videos/interview/articleid/52567/machine-learning-with-susan-nash Feel free to ask questions in the comments under the video, to be addressed in the future editions of the Podcast.
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16 Apr 2019 02:56 PM |
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0 Replies and 373 Views
Takeaway from Playmakers Series / Moneymakers Forum @OKC 373 0
Started by Patrick Ng
Takeaway - expect shifting landscape and limiting capital for the next 3 years. Reasons being: 1) Binge on leasing and flipping is over. Consolidation is happening. 2) Focus on returns and cash flows. Running a business for the long haul (vs. transacting in and out). So the Panel's exchanges on: a) Minimize frac hits (interference) - combine analytics and in-situ experiments, pave the way to reduction of plugs with diverting agents, eventually lead to potential savings of $ 450,000 to ...
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05 Apr 2019 11:48 AM |
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0 Replies and 308 Views
Automated Machine Learning vs ML causing crisis 308 0
Started by Patrick Ng
Fine tuning ML model is made easy with Azure’s automated ML (link: https://azure.microsoft.com/en-us/blog/announcing-automated-ml-capability-in-azure-machine-learning/ ) While it is the opposite end member to “ML causing science crisis” (February 20, 2019 post), the real question is whether we learn with the machine, or outsource learning to the machine with “No need to “see” the data'. For gut check, how about auto-nose correction algorithm on the 737...
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23 Mar 2019 12:00 PM |
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2 Replies and 367 Views
Machine Learning causing science crisis? 367 2
Started by Patrick Ng
'Machine-learning techniques used by thousands of scientists to analyse data are producing results that are misleading and often completely wrong.' Link: https://www.bbc.com/news/science-environment-47267081 According to professor Allen from Rice University, Houston, “answers they come up with are likely to be inaccurate or wrong because the software is identifying patterns that exist only in that data set and not the real world.” Crisis Not quite. Pe...
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