English
Beginner
12h
Probabilistic machine learning has gained a lot of practical relevance over the past 15 years as it is highly data-efficient, allows practitioners to easily incorporate domain expertise and, due to the recent advances in efficient approximate inference, is highly scalable. Moreover, it has close relations to causal inference which is one of the key methods for measuring cause-effect relationship of machine learning models and explainable artificial intelligence. This openHPI course will introduce all recent developments in probabilistic modeling and inference. It will cover both the theoretical as well as practical and computational aspects of probabilistic machine learning.
16h
Beginner
Free
1d
Intermediate
Free
1d 12h
Intermediate
Free
1d 8h
Intermediate
Free
12h
Beginner
Free
12h
Beginner
Free
12h
Beginner
Free
12h
Beginner
Free
Black Swan s.r.l. - Via Guerrazzi, 8 - 20900 Monza (MB) - PIVA / CF: 09991210965
