Teaching GuideTerm Faculty of Computer Science |
Máster Universitario en Intelixencia Artificial |
Subjects |
Machine Learning II |
Learning aims |
Identifying Data | 2022/23 | |||||||||||||
Subject | Machine Learning II | Code | 614544014 | |||||||||||
Study programme |
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Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
Official Master's Degree | 2nd four-month period |
First | Optional | 3 | ||||||||||
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Learning outcomes | Study programme competences / results | ||
To acquire knowledge of how the main incremental learning techniques work. | AC10 AC11 AC12 AC15 |
BC2 BC3 BC4 BC5 BC6 BC7 BC8 BC9 |
CC3 CC4 CC7 CC8 CC9 |
To apply incremental learning techniques for the analysis of real-time data in stationary and non-stationary environments | AC10 AC11 AC12 AC15 |
BC2 BC3 BC4 BC5 BC6 BC7 BC8 BC9 |
CC3 CC4 CC7 CC8 CC9 |
To know the working principle of the main privacy-preserving learning paradigms | AC10 AC11 AC12 AC15 |
BC2 BC3 BC4 BC5 BC6 BC7 BC8 BC9 |
CC3 CC4 CC7 CC8 CC9 |
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