Gradient descent with Momentum - Week 2

[TMosh]

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Momentum Formula

Here is the formula for momentum gradient descent in the week assignment which passed the test: on itiration of l from 1 to L+1 v[“dW”+str(l)]=betav[“dW”+str(l)]+(1-beta)grads[“dW”+str(l)] v[“db”+str(l)]=betav[“db”+str(l)]+(1-beta)grads[“db”+str(l)] parameters[“W”+str(l)]=parameters[“W”+str(l)]-learning_ratev[“dW”+str(l)] parameters[“b”+str(l)]=parameters[“b”+str(l)]-learning_ratev[“db”+str(l)] And all the vdW1, vdW2… are all set to zero initially. what I find by itirating l is that v doe…