Introduction to Probabilistic Machine Learning (ST 2023) - tele-TASK
Prof. Dr. Ralf Herbrich
- 12
- Episodes
- 2023
- First episode
About Introduction to Probabilistic Machine Learning (ST 2023) - tele-TASK
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 relationships of machine learning models and explainable artificial intelligence. This 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. In the course, we will implement all the inference techniques and apply them to real-world problems.
- Publisher
- Prof. Dr. Ralf Herbrich
- Category
- education
- Language
- en
- Explicit
- No
- First episode
- 17 Apr 2023
- Latest episode
- 17 Jul 2023
Latest episodes
12 episodes in the feed.
17 Jul 2023
Applications
10 Jul 2023
Bayesian Ranking
3 Jul 2023
Graphical Models
26 Jun 2023
Bayesian Classification & Graphical Models
19 Jun 2023
Bayesian Classification (2)
12 Jun 2023
Bayesian Classification
5 Jun 2023
Bayesian Regression (2)
22 May 2023
Bayesian Regression
15 May 2023
Linear Basic Function Models
8 May 2023
Information & Inference (2)
24 Apr 2023
Information & Inference
17 Apr 2023
Probability
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