I ran couple of simple ML examples available from the Documentation.
A small data set with less than 100 records would take a whole 10 sec to be trained in my laptop.
If I have a new set of sample data of 100 records available every hour, do I need to add those records to the population and train the entire Classifier all over again every hour? Is Classifier capable of retaining of its previous trained knowledge, while we keep feeding in newly available set of data to the Classifier every now & then?
On the site:
John McLoone explains the ML framework. In part 7 of the lecture at 3:25 minutes he shows that you can add data in a already trained network.