Excel-Based Random Forest Machine Learning Algorithms: Programming and Application
Part of AAPG’s GeoAnalytics Credentialing Program, this two-day online AAPG Short Course, Excel-Based Random Forest Machine Learning Algorithms: Programming and Application, is set to take place 14–15 April 2020 for web-based participation only.
At long last, sophisticated machine learning has arrived in Microsoft Excel for direct application to on-the-job workflows. Learn how to build and use machine learning with the powerful and flexible Random Forest algorithm using Microsoft Excel. This short course will provide hands-on guidance and coaching potentially saving your company thousands of dollars and weeks or months of production time.
- Why This Course Stands Out
You Keep the Tool – The Random Forest tool that is developed in the class and its master copy from the instructor are production-ready and will be given to all attendees.
- The Course is Built for You – There are many courses teaching software engineering and data science. Rather than dilute the lessons in order to teach to a general audience, this course has been built for an oil and gas attendee skillset and use cases. All examples and exercises will reflect common workplace problems faced by attendees.
- Move Quicker in Excel – Learning to deploy Random Forest can take several weeks of training in graduate data science programs, but this course makes use of your existing knowledge of Excel to accelerate the learning. You can also skip all the parts about learning to create a robust back end and just rely on Excel spreadsheets for data storage.
- Random Forests Add Considerable Value – Random forests are widely applicable, do not require extremely large data sets, can be used for both regression and categorization, and are typically capable of yielding high accuracy results without extensive tuning. They are generally not available in Excel, but this workshop makes them so.
- Understand Every Step – Rather than teach advanced data science methodologies using off-the-shelf tools that do not allow visualization of intermediate steps, this course deliberately pushes all intermediate output into Excel, making it easy to see, understand, trust, and adapt everything created in the course for deployment on the job.
New! Online Participation
This course will be available for online participation only offering the same knowledge and educational experience as if attended in-person. Supplemental materials and personal interaction with the instructor will follow the course to help perfect the tool and coding, as well as testing the Random Forest tool on real-life data.
Hear from the instructor and get a sneak peak into the course.
(Watch Now)
