SC5: An introduction to machine learning and data analytics

SC5: An introduction to machine learning and data analytics

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Key concepts to be discussed  at the workshop will include:

Mineral exploration and mineral deposits are often data-rich environments. Data-driven geoscience can be an effective method of resource discovery and mineral deposit modelling. This short course will introduce geologists to the growing field of machine learning / data analytics, for exploration and mining geology.

The morning sessions will acquaint attendees with essential topics such as the ‘closure issue’, applying ratios and log-ratios to compositional data, multivariate methods including principal component analysis, clustering and classification, and uncertainty measures. The afternoon session will provide a practical exercise(s) related to data analytics in geochemistry and will consider real-life datasets with workflows

The purpose of this course is to provide geologists with the understanding to ask what kind of data analytics is best-suited to their problem, and to demystify this growing field by providing the tools for them to conduct their own simple data analytics.

Click here to download a PDF version of the information for this short course.

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6 April, 2019


8.00am - 5.00pm


University of Auckland, NZ


NZ $250 Member

NZ $300 Non Member

NZ $50 Student


Morning and afternoon teas and lunch