As a practical example, brain.js is a very limited neural network library. You can only provide a dataset and train on that dataset. You can't implement any variations like dropout, stochastic gradient descent, momentum, etc.

Whereas a good neural network library like Torch lets you work at a much lower level of abstraction. You can put together individual layers, and it gives you the internal code for doing forward and backward passes, and chaining them together.