Continuous Experimentation Goes Brrr
Making ML experimentation fast and efficient through automation and better defaults.
A talk at PyData Riyadh about the gap between having an idea and knowing whether it works — and how much of that gap is infrastructure rather than thinking.
I built a continuous experimentation pipeline live on stage, from empty repo to tracked results. The working example is on GitHub: ma7dev/simple-ce-example.
Mazen Alotaibi (@ma7dev)