Federico Raimondo
Team leader at the Institute of Neuroscience and Medicine (INM-7) and research software engineer for various software projects, among them julearn.
Building, evaluating, reproducing and interpreting ML models from neuroimaging is not easy. julearn enables domain experts without highly developed programming and technical skills to analyze brain images and build complex ML pipelines, while neuroimaging and ML experts can easily extend the libraries with custom methods. At the same time, julearn prevents typical user errors, in particular bias caused by data leakage.
Advantages in brief:
An overview of julearn is also available as an easily digestible leaflet: Download Flyer