Introduction to Machine Learning

7.5 credits

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

Växjö

Linnaeus University’s campus is located roughly 15 minutes with bicycle from the city centre. Campus is like a small society in its own right, with the university, student accommodation and student life all in one place. Everything happens on campus – here you become part of a creative knowledge environment and an eventful student life.

What will you find when exploring Växjö? There is a great selection of restaurants and cosy cafés. There is a large lake in the city centre, beautiful nature is always nearby. Many students enjoy the combination of the city centre in Växjö and life on campus. This is where your dream of the future begins!

Students