101: Machine Learning – Case Study

In this podcast, Susan Havlin, Managing Consultant APAC and Dr Gregory Zhang, Senior Geology Consultant discuss the application of machine learning for geological domaining in Resource Estimation, with specific reference to a project that Dr Gregory Zhang worked on.

This podcast at a glance:

1.21 A case study using the k-means algorithm

0.55 Why was an alternative approach needed?

2:10 What is the k-means algorithm and why is it suitable?

3:10 What steps were used to apply k-means to the data set?

4:20 What were the key outcomes?

5:20 Any limitations?

7:40 Speed of getting results

8:12 Who can use this method?

If you'd like to connect with Susan Havlin and Dr Gregory Zhang, please email them: contact@snowdenoptiro.com

This audio podcast is also available as a free video podcast on Snowden Optiro’s YouTube channel.

Snowden Optiro is a resources consulting and advisory group that provides independent advice, consulting and training to mining and exploration companies, their advisors and investors. We help mine developers to advance their projects, mining companies to improve their operations and their professionals, and investors to de-risk their investments by the provision of quality advice, training and software in the field of Mineral Resources and Mineral/Ore Reserves.

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contact@snowdenoptiro.com