Operationalizing data science projects is not an easy task — it becomes twice as hard when teams are isolated and playing by their own rules. This guidebook bridges the gap for a smoother way to push data projects to production.
A brief overview of ways in which operationalization can be promoted (and used) within your company
Discussion on topics ranging from Best Operating Procedures to Risk Management for unforeseen situations
A deep look into modeling strategies and the implementation of communication strategies