Uncertainty in Machine Learning. Real production cases: automatic metal welding, dialogue assistant, self-driving car

Recorded videos from the Open Data Science conference

Ivan Provilkov, head of machine learning at Steinbeis Consulting Center AI (STAI) has published several videos about uncertainty estimation. In the next videos, you will find the latest use cases of machine learning uncertainty estimation techniques, industry benchmarks & applications.

Ensemble Distribution Distillation - Regression

In this video, we will see how Ensemble distribution distillation could be adapted to a regression task. We will introduce Regression Prior Networks and will see the results of Ensemble distribution distillation on depth estimation task.

Ivan Provilkov: Application Case Study

In this video, we will go through 3 case studies of how uncertainty estimation can be applied in real production cases: automatic metal welding, dialogue assistant, and self-driving car.

Tutorial on Uncertainty Estimation

We will go through the python implementation of uncertainty estimation ensemble methods. On easy tasks, you will learn how to use algorithms proposed in our videos for classification and regression. We will see how to compute and use different types of uncertainties for different cases. The code is publicly available, and you can use it in your projects: https://github.com/VProv/uncertainty_example

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