Vak: Applied Machine Learning credits: 5
- Vakcode
- SEVM19AML
- Naam
- Applied Machine Learning
- Studiejaar
- 2024-2025
- ECTS credits
- 5
- Taal
- Engels
- Coördinator
- S.S. Ahmed
- Werkvormen
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- Hoorcollege
- Projectonderwijs
- Toetsen
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- Applied Machine Learning - Opdracht
Leeruitkomsten
At the end of this module the student will reach the following learning outcomes:
- The student can analyse a data analysis task and compare features to evaluate their fitness for the machine learning task at hand.
- The student can evaluate whether a data analysis task requires dimensionality reduction, blind source separation, cluster analysis or classification.
- The student can interpret high dimensional data using dimensionality reduction techniques such as principal component analysis.
- The student can interpret multi-sensor data:
- using blind source separation techniques like independent component analysis.
- using cluster analysis techniques like hierarchical agglomerative clustering and k-means.
- using classification algorithms like support vector machines.
- The student can apply anomaly detection on a stream of sensor data.
Inhoud
The course covers the following topics: machine learning overview, dimensionality reduction, blind source separation, cluster analysis or classification, coverage plot, confusion matrix, cost functions.
Opgenomen in opleiding(en)
School(s)
- Instituut voor Engineering