An overview of best practices for implementing ML systems - Part 1
In this series of blog posts, we will recommend some best practices identified from our own failures and successes throughout our time implementing machine learning (ML) systems. We won't discuss ML techniques here, but instead, provide an upper-level overview of how we design and develop ML products. Google offers a guide which elaborates on this topic: https://developers.google.com/machine-learning/guides/rules-of-ml/ . This series is comprised of three blogs. First, we will discuss the initial steps and the first pipeline. Second, we will elaborate on evolving the initial pipeline and third, we will present troubleshooting the pipeline and final adjustments.