deep learning is only applicable to some problems e.g. speech recognition and image classification where there is mountains of data to train many network parame

deep learning is only applicable to some problems e.g. speech recognition and image classification where there is mountains of data to train many network parameters but also a certain level of complexity in the features. Most simple problems with a few thousand feature vectors for training are still solved by SVMs etc. Deep learning is getting excellent results in the problems it is good at though, better than any other classifier. Remember SVMs were being thrown around as the ML wunderkind prior to Deep learning. After a while people figure out exactly what some things are good at and some things not so good.