Advanced Machine Learning2016HT
No of lectures
Still to be decided, but approximately 5-10 lectures and 3-4 computer labs.
PhD students in Statistics, Computer Science, Applied Mathematics, and related engineering sciences.
The course was last given
Learning about some commonly used probabilistic machine learning models, such as Bayesian networks, State-space models, and hidden Markov models.
- Introduction to Machine Learning, 6 hp, or equivalent. It is ok to take this
course simultaneously with the Advanced course.
- Bayesian Learning, 6 hp, or equivalent.
- Some knowledge of MCMC methods (similar to what is included in the course Bayesian learning).
Lectures and computer labs.
Bayesian networks, State space models, Hidden Markov models.
Pattern recognition and machine learning by C.M. Bishop, ISBN 9780387310732.
Mattias Villani, Oleg Sysoev and José Pena.
Mattias Villani/José Pena
This course is also given at the master's programme Statistics and Machine Learning and at the Machine learning and AI profile on the civil engineering programme in Software engineering.
Page responsible: Director of Graduate Studies
Last updated: 2012-05-03