MNE459

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MNE459 - Machine Learning for Mining Applications

Mining & Geological Engr Undergraduate UA - UA General

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