Author Dan Darnell

Predictive models learn patterns in training data and use that information to predict target values for new data. There are two data sets at play in this process, the training data and the scoring or inference data. The model will work well in production (i.e., produce accurate predictions in line with expectations) when the new inference data is similar to…

The truth is that the work of data scientists cannot generate value if the models never make it to production. For data scientists writing custom models in languages like Python and R, the number of challenges for getting models into production can be overwhelming. Issues range from how to deploy model code on production systems, how to monitor performance, and…