BroadMole98

I'm still exploring what trains is for.

I guess you can think of Trains as Experiment manager + MLOps tied together.

The idea is to give a quick and easy way to move from coding/running on one machine to scaling it to multiple remote machines, with everything that comes with it.

In some ways it is like snakemake, it setups your environment and execute the code. Snakemake also allows you to setup data, which in Trains is done via code (StorageManager), pipelines are also done via code in Trains. Lastly Trains comes with a built in agent (trains-agent) and scheduler (including UI) that lets you connect any machine to your cluster (It can also run on top of K8s).

I'm pretty sure we can marry the two of them, but I need more information on the specific use case to come up with a clean solution :)