CSC300 Practical Machine Learning

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CSC300 Practical Machine Learning

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Not offered until Semester 1 2022 This course is a practical introduction to machine learning and deep learning. It introduces a variety of learning algorithms and how to use them. It covers key stages of the machine learning process such as algorithm selection, feature selection, model building, diagnostics, cross validation, and testing.

Other information

Prerequisite:
CSC201 and MTH212
Semester of offer: *
  • Petrie: Semester 1
Units:
12.00
EFTSL:
0.125
Student contribution band:
Band 2
Census date:
Academic Calendar

* Semester of offer is subject to change.

Course outline

The outline for this course is currently unavailable.

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