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So these are the steps to compute the forward propagation of our neural network.

2
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Over here we are using the function g to denote an activation function.

3
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Back propagation involves computing the derivative with respect to our parameters so that we can use

4
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that derivatives to update our parameters.

5
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Um that's a summary of the um the equations we've seen so far.

6
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And over here we are using the vector ization method of course out.

7
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I would advise you post a video over here and make sure you recognize the equations.

8
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If I have any questions just let me know and actually see you in the next lesson.