I actually would love to play around with Machine Learning but not on Azure - unless it's about training very big models - as this would rather make me poor rather quickly.
The issue is for me: I haven't figured out yet how to use it in a sensible way because if I had I would skip all this Node Red / Apache Spark / Flink / Kafka stuff and point some sensors directly to MSSQL Server. I do have a potential use case but at the current stage of the project and SQL Server Version I wouldn't want to invest the time into this, SQL 2019 Big Data Cluster might change that a bit but right now I'm not exactly holding my breath about eventually running a big fat SQL Server with GPGPUs in it.
Things look more like using Single Board Computers (like Raspberry Pi, Nvidia AGX Xavier) and TPUs (like Intel Neural Compute Stick, Google Coral USB Accelerator) is the way to go which leaves us with not many things you might want to process somewhere else - at least in case of sensor data I believe, a GIS where your trucks' route to the next manufacturing plant could be changed in real-time to avoid traffic jams is something I think Machine Learning on R & MSSQL Services is suitable for.
My workload is 100% on-prem, too well mostly. There is some PowerBI Project coming up which brings in the possibility of Azure even tho we're definitely going to deploy local Reporting Services.