Setting up a Machine Learning Framework for Production

Here at Hootsuite we're always looking for better ways to utilize our time and new technology. That's why we're looking at building an environment that helps developers leverage machine learning (ML) in production and minimize the overhead (i.e. Currently, ML is often done on a very ad-hoc basis. That's because there is no standardized workflow--as of yet--to deal with many of the unique difficulties associated with ML. Given the complexity of ML systems, it's unsurprising that they can contain some areas of technical debt. What was surprising to me however, was the sheer number of ways that that technical debt can arise.