Learning vs. training

Question

In my head, these two words (learning and training) seem to somehow have a fuzzy boundary between them.

For example, the word learning for me conveys the idea of training; if I want to learn something, I train myself in it!

When talking about machine learning algorithms, this happens too. I often find myself wondering if it's right to say "unsupervised training"! since, in my head, the word training is tightly related to supervised learning (here too can I say supervised training!).

Is there a clear boundary I can learn or should I just train myself the words' uses as they are :-)

Answer 1

Learning comprises the whole process, which includes a training step. There are another steps that differ from the initial learning, for example, learning reinforcement, when you re-train the model with new observations and data preprocessing.

To give you an example, lets say you have a dataset and you r model is a linear regression, the goal is to find some constants a and b that give you the best estimate of some observed outcomes. To train this model you can use different approaches: gradient descend, the explicit formula, genetic algorithms, you can train it using cross validation, using the complete dataset, etc.