Speaker
Lorenzo Moneta
(CERN)
Description
In the hands-on session we will present machine learning software such as Keras to build and train deep learning model
We will show an example of event classification using open simulated data of an LHC experiment and an example for building a generative adversarial network (GAN) to generate images.
The hands-on session will be run in Python using the CERN SWAN service.