Machine learning offers several algorithms, each tuned to solve individual and specific problems. By drawing parallels between computer sciences and geosciences to apply developed approaches to geoscientific data, Mira Geoscience offers several examples of the value-added of using machine learning and predictive modelling.
In three hours, learn how to get data from Geoscience ANALYST‘s free 3D viewer to Python and perform unsupervised learning on different types of data. The following applications will be seen:
- Automated geological mapping using K-Means and Self Organizing Maps
- Geochemical classification and interpretation using Hierarchical Clustering
- Structural Data interpretation
This masterclass is for beginners, but you do need basic knowledge of Python language. We will be offering intermediate and advance levels too! If you are interested let us know support@mirageoscience.com. $300 CAD (+ applicable taxes).
The class is divided into three 1-hour webinars and comes with all the necessary ppts, data, and workspace.
You will have to install Geoscience ANALYST and Anaconda (Python distribution) with the following packages: NumPy, pandas, Matplotlib, scikit-learn, and apsg. Instructions and Zoom links will follow registration.
About the host:
Jean-Philippe Paiement, P.Geo.
Director, Global Consulting
Jean-Philippe is our Director of Global Consulting. He brings 15 years of mineral exploration experience including expertise in geostatistics applied to structural, geological, and geochemical modelling and interpretation, specializing in non-linear interpolation and simulation. Jean-Philippe has developed multiple workflow and novel approaches to reduce interpretational risks of geological data. He has a wide range of experience in mineral resource estimation for precious metals, base metals and industrial minerals across diverse geological environments around the world. In 2016, Jean-Philippe has pioneered the application of Machine Learning to the mineral exploration industry in winning the Integra GoldRush challenge by application of machine learning to mineral deposit targeting. He is skilled in the application of machine learning to overcome geological and geophysical challenges by combining geological knowledge and both supervised learning and deep learning. Before joining Mira Geoscience, he obtained an MSc from Laval University. Jean-Philippe is based in Quebec-City.
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