Hello R-SIG-EPI members
Last chance to join our 1-day seminar Machine Learning for Computational Biology 2.0 livestreaming January 13 with Nikolay Oskolkov (Group Leader (PI) at LIOS). This workshop introduces machine learning techniques for analyzing complex datasets, offering advanced methods to complement traditional statistical approaches in epidemiological research. Participants will gain practical skills in R and Python to implement algorithms such as random forest, k-means clustering, and MCMC, which are invaluable for identifying disease patterns, predicting outcomes, and modeling complex risk factors. These hands-on capabilities will empower researchers to develop more sophisticated analytical tools and enhance the robustness of their epidemiological studies.
Sign up today (https://instats.org/seminar/machine-learning-for-computational-biolo) to secure your spot, and feel free to share this opportunity with colleagues and students who might benefit!
Best wishes
Michael Zyphur
Professor and Director
Instats | instats.org