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.
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Last Post 03 Mar 2020 11:11 AM by  Susan Nash
Excel-Based Random Forest Machine Learning Algorithms: Programming and Application
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Susan Nash
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03 Mar 2020 11:11 AM
    Check out the link:

    To give you a powerful new tool for your reservoir, reserves, supply chain, water management, and other models, AAPG is offering a machine learning course that jump-starts you into building powerful Random Forest algorithms without having to program in Python or R. You simply use Excel and Visual Basic, and your instructors will guide you as you build a tool you can use immediately, as well as keep for your use in the future.

    Most exciting of all, you can log in and participate in the course synchronously online if you cannot travel!

    Taught by Stanford and machine learning applications expert Alec Walker, Excel-Based Random Forest Machine Learning Algorithms: Programming and Application, will take place April 14-15 from 8 am – 6 pm each day. Face-to-face training will take place at the Marathon Energy Center in Houston, Texas. The course will feature post-training personalized follow-on coaching and coding debugging for the online and face-to-face participants. (To register, please click here.)
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