[SUB EN/FR] Logistic regression with scikit-learn in Python | Task 2 | Master Course AI4Omics

Github Repository: Presentation of the practical session: Task 2 – Solution and explanations This video presents a practical session of the Master Course Unit “AI for Omics Data Integration” of the University of Grenoble Alps. It is a part of the Master Program “AI4OneHealth”. The objective of this session is to develop practical skills in omics RNA-seq data analysis using machine learning techniques. We use Python programming language and the machine learning framework scikit-learn. The exercises will be present in a format of Jupyter notebooks. This video includes the explanations of the second task that proposes you to create a logistic regression classification model for colon cancer diagnosis. Presented by: Ekaterina Flin, EpiMed group, Institute for Advanced Biosciences (IAB), University of Grenoble Alps (UGA) #logistic_regression #scikit_learn #omics Timeline 00:00 Presentation of the Task 2 00:23 Import packages