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0 Replies and 448 Views
Deep Learning - LSTM for time series data 448 0
Started by Patrick Ng
For those working with production history / decline curve or well economics, this is of particular interest. https://courses.nvidia.com/courses/course-v1LIL-FX-24V1/courseware/002fd0d3d1a749a6956eaeac5a360926/5f0c98b68a7f48d6ae4a4d4f42657c50/activate_block_id=block-v13ADLI2BL-FX-242BV12Btype40sequential2Bblock405f0c98b68a7f48d6ae4a4d4f42657c50 Cost $30 goes to zero if you are a SEG member and access registration via SEG Deep Learning, with promote code (click button SEG30). Pe...
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03 Feb 2021 12:12 PM |
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0 Replies and 462 Views
Energy in Data 2021 - Altogether Immersive and Interactive Experience. 462 0
Started by Patrick Ng
https://energyindata.org/ AAPG-SEG-SPE kicks off 2021 with a all-digital immersive and interactive joint event online. We have heard from AI/ML workshops over 2019-2020 that members express interest in creating a community to advance knowledge and share experience on their digital journey. EiD 2021 has taken the first step, and to build out the community, it is only a click away. Go online and register today.
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12 Jan 2021 02:52 PM |
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0 Replies and 819 Views
AlphaFold 2.0 819 0
Started by Andrew Munoz
DeepMind has made some major upgrades to AlphaFold because they are now able to successfully predict protein folding. This is going to be a major leap for using predictive analytics for disease research. I think it's great for everyone to know and understand leaps in deep learning in all fields. Naser Tamini has a great Medium article simplifying the result and explaining the solution: https://tamimi-naser.medium.com/unfolding-alphafold-683d576a54a3 I hope you enjoy! Andrew
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03 Dec 2020 06:05 PM |
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0 Replies and 459 Views
Highlights on Tackle the Issues - Where should Machine Learning go (and not go)? 459 0
Started by Patrick Ng
Observations - Dr. Lian and speaker Ball showed in examples simple architecture, random forest (RF) and support vector machine (SVM) work well in many cases (some as good as deep learning models). Q1: what does that tell us about ML model - simplicity vs complexity, and the direction Recap - much has to do with data / sampling. If we have lots of data, deep learning will do well. When we have limited data, RF and SVM may perform better (in supervised and unsupervis...
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02 Oct 2020 05:21 PM |
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0 Replies and 444 Views
Business Acumen, Soft Skills and Machine Learning 444 0
Started by Patrick Ng
In the opening Michel T. Halbouty Lecture: Business Acumen and Soft Skills in an Everchanging Exploration World Day: Duval talked about “soft skills” now considered all the more important since the “engineering” preparation of a prospective deal and the related technologies are and will be more and more dependent on data analytics, advanced approaches involving AI, machine learning, etc. Takeaway - two ML questions were raised in Chat, worthy of recap here. Q1: if you have physics based mo...
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02 Oct 2020 01:53 PM |
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