Organisation of machine learning webinars

During this period of lockdown, our statistician team stays connected and works together to share their different knowledge in data analysis.

Since May 2020, webinars are regularly organized. A different topic is proposed each time, starting with a theoretical presentation followed by a practical demonstration with concrete examples studied by our partners.

The first workshops mainly concerned the use and analysis of data through the programming language R widely used by statisticians.

  • Laura Dale (LKV BW) started this series of webinars by presenting the spectra prediction of energy balance data at the LKV-BW;
  • Rshiny, a visualization tool for creating interactive web applications, was presented by Marion Calmels (FCEL, Seenovia);
  • Fatima Ezzahra Bouzidi Idrissi (FCEL) intervened to explain an algorithm widely used in machine learning, Random Forest;
  • An introduction to Deep Learning was given by Mohammed El Jabri (IDELE).

Another programming language, Python, was covered during the webinars:

  • The Deep Learning method was treated through the example of carcass image analysis by Daragh Matthews (ICBF);
  • While Urs Schuler (Qualitas) showed us how the incorporation of spectral predictions of acetonemia are included in genetic evaluations at Qualitas.

This exchange of knowledge is very enriching for everyone and for the success of the project. More virtual meetings are already scheduled for the coming months!

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