Machine Learning

Utbildningsfakta

Kod: 2DT916

The course covers machine learning concepts and methods. The following topics are covered in the course: basic statistical concepts supervised and unsupervised learning linear and polynomial regression, logistic regression decision trees Support vector machines unsupervised learning using the k-means clustering algorithm algorithm evaluation using cross-validation and mean square error evaluation metrics such as precision, recall, and F-score algorithm implementation using MATLAB

Behörighet

60 credits including 7.5 credits of Linear Algebra (e.g. 1MA901 or equivalent) 7.5 credits of Appliead probability and statitics (e.g. 1MA915 or equivalent) 7.5 credits of Programming (e.g 1DT901 or equivalent)

Utbildningstillfällen

Varje tillfälle har egna datum och villkor. Avslutade tillfällen behålls som historik och innebär inte att en ny ansökan är öppen.

• Machine Learning

  Linnaeus University (Kalmar Växjö)

  VÄXJÖ

  Startdatum: 29 mars 2027

  Slutdatum: 6 juni 2027

  Studietakt: 33 %