Machine Learning in Practice (intermediate level)

Date: 28th, 29th, 30th May 2024, Time: 9:00-12:00 each day

Location: Seminar room 1.65, Center for Molecular Neurobiology Hamburg (ZMNH), Falkenried 94, 20251 HH

Lecturer: Robin Khatri, Institute of medical systems biology, UKE

Language: English

Description: This workshop is open to students, researchers, and clinicians wanting to learn how machine learning is applied for biomedical datasets, the different classes of machine learning algorithms that may be used, as well as the best practices in selecting and evaluating algorithms, and their limitations.  The aim of the course is to provide concepts and tools to navigate the use of machine learning in the biomedical landscape. The course will use biological datasets and there will be hands-on components as well as discussions. Participants should already have taken an introduction to machine learning and be familiar with Python programming. The workshop will be in presence and therefore each participant should bring their own laptop (no ipads).


  • Taxonomy of machine learning algorithms
  • Linear regression, logistic regression and related methods
  • Decision trees
  • Support Vector Machines
  • Bias & Variance, curse of dimensionality
  • Representation learning
  • Neural networks and deep learning: MLPs, transformers, CNNs
  • Applications to RNAseq and imaging data