This section of the ML-INFN Confluence Space contains the Knowledge Base of fully implemented use cases. This has been created in order to provide new users getting close to Machine learning with concrete examples, with step by step guides for reproducibility.

The division into categories is multidimensional 

• Dimension 2: per Machine Learning technology (CNN, Auto encoders, LSTM, GraphNet, ...)
• Dimension 1: per scientific field (High Energy Physics, Gravitational Waves, Medical Physics, ...) 
• Dimension 3: per type of used tool

and is implemented via Confluence labels.

Table of Use cases