What do you call a machine learning system that keeps on learning? As I understand it from this video lecture, there are three types of deep learning:


Supervised
Unsupervised
Reinforcement


All these can serve to train a neural network either only prior to its deployment or during its operating. 

For the latter case, it is referred to as continuous learning here and here and as dynamic learning here and here.

Which term should I use to refer to a machine learning algorithm that keeps on learning (even after deployment)? If it's "continuous", is there an opposing term (such as "static" for "dynamic") for those systems that stop learning before being deployed?
There are several terms or expressions related to such systems, such as online learning, incremental learning, continuous learning, continual learning, and lifelong learning. They are sometimes used interchangeably, but some of them have slightly different meanings. For example, online learning does not need to be incremental, which refers to algorithms that attempt not to forget previously learned information.

The opposite of online is offline. However, the expression batch learning is sometimes used as an antonym for online learning.