One example is, an early layer could possibly identify one thing as remaining in a specific condition; building on this understanding, a afterwards layer could possibly be able to establish the shape for a prevent indicator. Comparable to machine learning, deep learning works by using iteration to self-proper and boost its prediction capabilities.