P000150, Introduction till Machine Learning, 4.0 Hp
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Kursplan

Nivå

Forskarnivå

Ämne

Matematisk statistik

Betygsskala

Engradig skala

Kraven för kursens olika betygsgrader framgår av betygskriterier, som ska finnas tillgängliga senast vid kursstart.

Kursspråk

Engelska

Behörighetskrav

Mål

The objective of the course is to provide an overview of machine learning methods. Upon completion, students will be able to:

• Identify and select appropriate predictive and classification models for various problems
• Implement machine learning models in R
• Apply cross-validation and resampling techniques for model assessment
• Interpret model results and evaluate their performance critically
• Communicate statistical findings effectively in written and oral form

Innehåll

The course will cover the following topics:

• Principles of machine learning: over- and underfitting, bias-variance tradeoff, cross-validation
• Tree-based methods: Decision trees and ensemble methods
• Artificial neural networks (ANN)
• Unsupervised learning: PCA and clustering

Examinationsformer

Passed exercises and passed examination in written and/or oral form.

Ansvarig institution eller motsvarande

Institutionen för energi och teknik

Kompletterande uppgifter

Övrig information

Literature:

Joint course literature is established separately and is listed in a supplement to the course syllabus. Current information about joint course literature shall be made available not later than eight (8) weeks prior to course start.