Random Initialization, Deep Learning.
will be either very large or very small. And so in that case, you’re more likely to end up at these fat parts of the tanh function or the sigmoid function, where the slope or the gradient is very small. Meaning that gradient descent will be very slow. So learning was very slow. So just a recap, if