Python Deep Learning

End-to-end evaluation

From a business point of view what really matters is the final end-to-end performance. None of your stakeholders will be interested in your training error, parameters tuning, model selection, and so on. What matters is the KPIs to compute on top of the final model. Evaluation can be seen as the ultimate verdict.

Also, as we anticipated, evaluating a product cannot be done with a single metric. Generally, it is a good and effective practice to build an internal dashboard that can report, or measure in real-time, a bunch of performance indicators of our product in the form of aggregated numbers or easy-to-interpret visualization charts. Within a single glance, we would like to understand the whole picture and translate it in ...