The rapid growth of artificial intelligence and data science has made scikit-learn one of the most popular Python libraries. The tutorial will present the main components of scikit-learn, covering aspects such as standard classifiers and regressors, cross-validation, or pipeline construction, with examples from various fields of application. Hands-on sessions will focus on medical applications, such as classification for computer-aided diagnosis or regression for the prediction of clinical scores.

Learning outcomes :

Ability to solve a real-world machine learning problem with scikit-learn

Prerequisites :

  • Basic knowledge of Python (pandas, numpy)
  • Notions of machine learning
  • No prior medical knowledge is required
Starts
Ends
CET
ICM
Institut du Cerveau et de la Moelle épinière Hôpital Pitié Salpêtrière, 47 Boulevard de l'Hôpital, 75013 Paris https://icm-institute.org/

How to go to ICM: https://icm-institute.org/en/access-map/

Registration to all PATC courses is free.

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