One of the good things with DL is that it extracts features without our intervention. The conventional ML algorithms need features to be extracted before using them.

At the end, it depends on your project and dataset

Another paper on the matter

One more

Marianne, Thanks for the link.

It depends on number of data sets. DL needs huge data set to train your algorithm to achieve good results. However, ML can work with small sets of data sets. DL takes less computational time compare to ML algorithm.