docs: Added more text regarding the classification entry.

README.md

@@ -9,6 +9,17 @@ This is a Julia implementation in Flux of the Evidential Deep Learning framework
 
 ## Classification
 
-![](images/threegaussians.png)
+Deep evidential modeling works for classification as well as for regression. In
+the plot below you can see the epistemic uncertainty as a consequence of
+position in the plot. The task is to separate three Gaussians in 2D. The code
+for this example can be found in
+[classification.jl](examples/classification.jl).
 
-More to come.
+![uncertainty](images/threegaussians.png)
+
+## Summary
+
+Uncertainty is crucial for the deployment and utilization of robust machine
+learning in production. No model is perfect and each and every one of them have
+their own strengths and weaknesses, but as a minimum requirement we should all
+at least demand that our models report uncertainty in every prediction.