in my experience, doing deep learning is a lot harder than building simpler ml models. training times are killer, need lots of data, overfitting is a challenge, hard to interpret results, lots of things can go wrong. deep learning is the future from a mathematical standpoint (with neural nets you can essentially learn arbitrary functions in some borel space or something whereas simpler ml models are basically a special case of deep learning) but it's definitely harder.
