Skip to Main Content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

INF 513 Machine Learning: Reading list

INF 513 Machine Learning 


Department: MSc in Informatics (Knowledge and Data Management) 
Module Description: Machine learning is about making computers learn, rather than simply programming them to do tasks. The course will discuss supervised learning (which is concerned with learning to predict an output, from given inputs), reinforcement learning (which is concerned about learning from interacting with an environment), unsupervised learning, where we wish to discover the structure in a set of patterns; there is no output "teacher signal". We will compare and contrast different learning algorithms, and unlike Data Mining Exploration module where the focus was on the applying algorithms to large real-world data sets, in this course we will get to the technical and mathematical details of the studied algorithms.

Module text(s)

The lecture notes are designed to be self-contained, with pointers to web-resources and related material. Recommended readings include

Chapters in the following books are interesting to read

Ask a Librarian for help to find and evaluate resources