The Stacked Up! series with Chris Alexiuk is a response to our MLOps World Committee’s concern about the lack of understanding and clarity around the tools, and ML stacks used across different ML teams, and application areas. As part of our mandate to give back to the ML community we’ve designed this series to be a non-commercial, open discussion around what tech companies use behind the scenes in order to help shed light for others working in the field.

There is no “one size fits all solution” or “perfect” stack. Often, core challenges centre around different factors; budget, data, models availability and a variety of other inhibitors specific to a given application area. The space can be ripe with options for solutions, but what works for some is completely unsuitable for others.

This is why conversations on the topic are important and helpful. What’s worked, what hasn’t, and how teams have landed on their current ML tech stack are important conversations that will help drive our ML community forward.

If this is something you’re interested in helping with – we look forward to hearing from you!