Machine Learning Python Course

Workshop

  • Beginn: 08.01.2025 09:00
  • Ende: 09.01.2025 16:00
  • Vortragende(r): Markus Hohle
  • Ort: Max-Planck-Institut für Mikrostrukturphysik, Weinberg 2, 06120 Halle (Saale)
  • Raum: Lecture Hall, B.1.11
  • Gastgeber: IMPRS-STNS
  • Kontakt: imprs@mpi-halle.mpg.de
Machine Learning Python Course
The aim of the course is to introduce you to the most common Machine Learning tools. These tools include classical methods such as Linear Models, standard methods like Trees and Support Vector Machines or more recent tools like UMAP or Artificial Neuronal Networks. The tools will be explained by discussing an hands-on example and by briefly working out the underlying mathematical idea.
    Target group: PhD students and postdocs
    Group size: max. 15
    Registration via imprs@mpi-halle.mpg.de

    About the lecturer

    Markus studied Physics in Jena and did his PhD at the MPE in Garching. After two years as PostDoc at the AIU Jena, he worked as fulltime lecturer at LMU Munich for 11 years. Since August 2024 he teaches Python courses and ML algorithms at UC Berkeley.

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