Web Reference: Jan 15, 2026 · To train deep neural networks effectively, managing the Vanishing and Exploding Gradients Problems is important. These issues occur during backpropagation when gradients become too small or too large, making it difficult for the model to learn properly. The inverse problem, when weight gradients at earlier layers get exponentially larger, is called the exploding gradient problem. Backpropagation allowed researchers to train supervised deep artificial neural networks from scratch, initially with little success. Dec 8, 2023 · We will now go through some techniques that can reduce the chance of our gradients vanishing or exploding during training. If you want to learn more about activation functions along with their pros and cons, check my previous post on the subject:
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