GammaLearn Release v0.7.4 The main changes in this release concern the automatization of the releases: publication to Zenodo, generation of docker containers and pypi packages. Changelog: - cleaner install and auto upload to pypi - Package nets and experiments example settings as package data - Include GammaPhysNet in GammaLearn - allow gammalearn --version - Autoencoders in glearn - Fix calls to .item() - Replace GpuStatsMonitor with DeviceStatsMonitor and accelerator with strategy - Zenodo automated publication of releases - using setuptools_scm to determine version from git tag and distance to tag - Documentation - Docker containers - Harmonise GammaLearn headline - Add metadata as codemeta file - fix classification metrics import

GammaLearn is a collaborative project to apply deep learning to the analysis of low-level Imaging Atmospheric Cherenkov Telescopes such as CTA. It provides a framework to easily train and apply models from a configuration file. Learn more at https://purl.org/gammalearn