MNE459
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MNE459 - Machine Learning for Mining Applications
Course Description
Recent advances in technology have enable mining companies with the ability to collect in near real-time large amounts of data. Machine learning represents a valuable set of tools to extract valuable information, synthetize predictive models, and overall contribute to a better understanding of many aspects of the mining operations. This class provides formal introduction to machine learning topics, with a specific emphasis in applications associated to the mining and minerals industry. First, a general overview of the machine learning methodology is provided, along with a description of the main architectures used in current applications. Emphasis is given to tasks such as data characterization, model selection and tunning, performance metrics, and validation strategies. The second part of the class is project-based and focused specifically on the development of a machine learning application for mining or geology problems.
Min Units
3
Max Units
3
Repeatable for Credit
No
Grading Basis
GRD - Regular Grades A, B, C, D, E
Career
Undergraduate
Enrollment Requirements
019179
May be convened with
MNE559
Name
Lecture
Workload Hours
3
Optional Component
No
Typically Offered Main Campus
Fall
Typically Offered Distance Campus
Fall
Typically Offered UA Online Campus
Fall
Typically Offered Phoenix Campus
Not Offered
Typically Offered South Campus
Not Offered
Typically Offered Community Campus
Not Offered