Why ML needs its own flavour of dev. methodology and a partial, draft proposal for such a methodology Photo by Denise Jones on Unsplash TL;DR ML teams working on complex projects need to battle the intrinsic challenges in ML, as well as the friction which arises from their multi-disciplinary nature which makes it hard to make decisions.

Over the last few years, many software organisations have started developing products which leverage machine learning. Like every new technology, ML involves a certain learning curve, and managing this learning curve is critical for a successful ML adoption.