Communicate Model Insights (6 types of information that should be…
Communicate Model Insights
6 types of information that should be communicated during a presentation
Model Quality Metrics
Areas where a model struggles
Most predictive features for model building
Features types especially interesting to management
Delving into foundational questions will not leave enough time remaining for the presentation
Recommended business actions
Explain that all the algorithms determine the generalizable relationship between features and the target.
Release the holdout data to validate the model
Two main types of data were discussed
There are four kinds of features to consider before going into a management presentation
Features that need to be changed and therefore require a re-run of the models
Features requiring further examination
Set up prediction system
Five different DataRobot model deployment strategies
Specific details will be passed over apart from the need to upload all relevant data in a file containing the features used to create the model.
Application programming interface (API)
Creates an approximation of the selected model available as code in the Python and Java programming languages.
Uses the DataRobot API to upload and score multiple large files in parallel.
In-place with Spark
allows for exporting the selected model as an executable file to be used in an Apache Spark environment