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Machine learning: what does that actually mean for a METS business?

This workshop is now at full capacity. To put your name on a waiting list, please email Eve Lippmann elippmann@etf.com.au

Dr Zygmunt Szpak, from the Australian Institute for Machine Learning, will deliver a workshop on the strategic opportunity for machine learning in business.

The overall aim of the workshop is to help participants identify the potential role of AI in their business.

Dr Penny Stewart, founding CEO of PETRA Data Science, will present case studies demonstrating the successful application of machine learning in mining.

Learning objectives

  1. Explain the conceptual difference between artificial intelligence, machine learning and deep learning.
  2. Outline the input and outputs for a typical machine learning system.
  3. Distinguish between supervised and unsupervised machine learning and recognise the different implications each has on data requirements.
  4. Articulate why machine learning techniques have been able to disrupt numerous industries.
  5. Appreciate the advantage of early adoption and the risk of complacency.
  6. Review several case studies where machine learning added value to the company.
  7. Pinpoint key moments where important decisions are made that could benefit from machine predictions.
  8. Use an ‘AI Canvas’ to explore how AI can be tailored to your business and support your decision making processes.
  9.  Able to conduct an audit of the data and data governance processes within a business to determine the readiness of an organisation to develop machine learning capabilities from their own data.

Learning outcomes

Participants will understand the opportunity and limitations of machine learning for their business and the mining sector. They will have been challenged to think about their role in capturing the value of machine learning from their industry sector for their business, and seen practical examples of application of Machine Learning from a leading Australian supplier.

Speakers and bios

Dr Penny Stewart

CEO PETRA Data Science

Penny is a mining professional and entrepreneur (BE Mining, PhD, RPEQ, AusIMM CP). In June 2015, Penny founded PETRA Data Science to engineer data science solutions for the resources industry. Penny and her team have developed a suite of highly scalable algorithms for the mining industry e.g. machine learning algorithms to predict equipment and process downtime/efficiency, and digital twin value chain optimisation. In 2016, PETRA collaborated with Newcrest Mining to develop and deploy some of the mining industry’s first machine learning algorithms.

Penny worked on mine sites for five years before obtaining her Queensland 1st Class Mine Managers’ Certificate of Competency in 2000. In 2000, she commenced PhD studies at UQ’s Julius Kruttschnitt Mineral Research Centre, where she received the Ian Morley prize for Best Minerals Engineering Postgraduate student. In 2009, she instigated the application of self-organising maps (neural networks) for the study of SLC recovery analysis. As a consultant rock mechanics engineer, she developed original regression and probabilistic models to predict geotechnical instability. In Newcrest’s Innovation Group 2011-2013, she combined her operational background with advanced analytical skills, to design and execute research and innovation projects.

Dr Zygmund Szpak

Australian Institute for Machine Learning

Zygmunt L. Szpak received his PhD degree in Computer Science from the University of Adelaide, Australia, in 2013, and his MSc degree in Computer Science from the University of KwaZulu-Natal, South Africa, in 2009. He is a senior research associate at the Australian Institute for Machine Learning and works on numerous industry inspired computer vision and machine learning problems. Most recently his work has focused on the application of machine learning and multiple-view geometry techniques for the development of smart medical devices. In particular, he was solely responsible for conceiving and developing an innovative hand-held wound assessment device in partnership with Labtech—a publicly traded company. The invention can categorise different wound tissue types and also report metric information such as the volume, area, and depth of the wound. A team of vascular surgeons at the Royal Adelaide Hospital have validated the utility and precision of the device in a clinical trial.

Where: Brisbane Convention & Exhibition Centre

When: Tuesday May 21, 2019

Time: 10am – 1pm

Fee: No charge

** Please note, this workshop is available for conference delegates only