An overview for getting up and running quickly and avoiding confusion From time to time, we all find ourselves considering whether to try out new tooling or experiment with a package, and there’s some risk involved in that. What if the tool doesn’t accomplish what I need, or takes days to get running, or requires complex knowledge I don’t have? Today I’m sharing a simple review of my own experience getting a model up and running using PyTorch Tabular, with code examples that should help other users considering it to get going quickly with a minimum of fuss.

An accessible tutorial for one way to put a model into production, with special focus on troubleshooting and hiccups you might encounter along the way As promised, this week I’m coming with a more technical topic and taking a little break from all the discussions of business. I recently had an opportunity to deploy a new model using AWS Lambda, and I learned a few things when combining my usual development tooling (Poetry) with the infrastructure of Lambda.