> For the complete documentation index, see [llms.txt](https://jmu-isgroup.gitbook.io/anomalydetection.ml/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://jmu-isgroup.gitbook.io/anomalydetection.ml/installation-and-use/1.-prerequisite.md). # 1. Prerequisite Requirements :desktop:**Hardware:** Our solutions was developed with minial requirements. given the use of non deep learning algorithms there are no hard hardware requirements. for relative small amounts of data a VM with 4C CPU and 8GB ram are more than enough. If you are eager to use our auto encoder implementation we recommend a more sophisticated system with at least 16GB VRAM.
:floppy\_disk:**Software:**\ We recommend the deploymend via Docker. Altough a baremetal deployment is possible, we designed our solution with containerization in mind. Our solution is a statless inference system. Theres no additional software needed, nor do we use additional docker containers. :test\_tube: **Test-system:**\ Ubuntu 22.04 with docker / docker-compose.