Introduction to recursive machine learning algorithms

Session 3. Applications

Thu, 26 Jan 2023 00:00:00 +0000

The session covered several example applications of the Kalman filter and parameter estimation via maximum likelihood. Participants presented their own problems and ideas. This was the final session of the workshop.

Session 2. Learning

Thu, 19 Jan 2023 00:00:00 +0000

The session covered the update step of the algorithm as shown in the sessions structure.

Session 1. Modelling

Fri, 13 Jan 2023 00:00:00 +0000

The session covered the prediction step of the algorithm as shown in the sessions structure.

About the workshop

Fri, 09 Sep 2022 00:00:00 +0000

This workshop is a “hands-on” introduction to machine learning methods that “use data as it arrives”. The algorithms update their internal states with every new piece of information, and produce estimates of non-measured or derived magnitudes. Some of the algorithms might revise the information already stored to improve those estimations.

Session 3. Applications

Fri, 15 Oct 2021 00:00:00 +0000

Session 2. Learning

Fri, 08 Oct 2021 00:00:00 +0000

The session covered the update step of the algorithm as shown in the sessions structure.

Session 1. Modelling

Fri, 01 Oct 2021 00:00:00 +0000

The session covered the prediction step of the algorithm as shown in the sessions structure.