Dear Colleagues, I have the pleasure to announce a refurbished and extended "Clustering and Classification with Python" course, part of my "machine learning"/"advanced statistical modelling" collection. The course provides a short introduction to the huge subject of clustering and classifying observations. We will apply these tools e.g. to discriminate between healthy and diseased states based on example genomic datasets. For more details visit https://training.vbcf.ac.at/training/pyclassif.php . Topics: - Hierarchical clustering, k-means clustering. - Gaussian mixtures, E-M algorithm. - Quadratic and linear discriminant analysis. - Principal Components Analysis (PCA). - Cross-validation techniques. - Logistic regression and its connection with discriminant analysis. Multinomial regression. Out of scope: We can cover only basic methodologies. I have no resources to discuss analysis of private data sets during the course. When? Two half-days on the 19th and 20th March (Thu-Fri), from 09:00 to 13:00 on both days. Where? IMP seminar room E-016. Pre-requisites: - Proficiency in Python. https://training.vbcf.ac.at/training/pylang.php - Familiarity with NumPy, Pandas (https://training.vbcf.ac.at/training/pydata.php) and a little bit of MatPlotLib. - Solid probability theory and statistics knowledge. - Knowledge of basic linear algebra concepts: vectors, matrices etc. Cost: Free of charge. How to register? Make sure you don't have any meetings on the days of the course. Then ask your boss for permission to attend, and sign up at https://training.vbcf.ac.at/training/schedule.php by filling out the little form. Sign up only if you are confident that you will attend, don't take away a slot from a colleague. Consult the general attendance rules at https://training.vbcf.ac.at/training/practical_information.php . You will get a confirmation from me later this week. Thank you, András