Transfer learning concept

The biggest problem, thoug h, is that models like this one are performed only on a single task. Future tasks require a new set of data points as well as equal or more amount of resources.

Transfer learning is an approach in deep learning (and machine learning) where knowledge is transferred from one model to another.

Deep learning models require a LOT of data for solving a task effectively. However, it is not often the case that so much data is available. For example, a company may wish to build a very specific spam filter to its internal communication system but does not possess lots of labelled data.

What you can do is using a pre-trained image classifier on dog photos to predict cat photos.