Towards Data Science, Neural Networks, Deep Learning, Machine Learning, Naturallanguageprocessing.
added. So gradient vanishing or explosion is rarely an issue. 1.3. RNN problem 3 — RNNs need larger training steps to reach a local/global minima. RNNs can be visualized as an unrolled network that is very deep. The size of the network depends on the length of the sequence. This gives rise to many