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Deep neural networks
Notation
$l = 4$ layers $n^{[l]} = \text{# of units in layer } l$
$n^{[0]} = 3$ $n^{[1]} = 5$ $n^{[2]} = 5$ $n^{[3]} = 3$ $n^{[4]} = n^{[l]} = 1$
Forward prop
Input: $a^{[l - 1]}$
Output: $a^{[l]}$, cache $(z^{[l]})$ and $W^{[l]}$, $b^{[l]}$
$Z^{[l]} = W^{[l]} A^{[l-1]} + b^{[l]}$ $A^{[l]} = g^{[l]}(Z^{[l]})$
$A^{[0]}$ is input set.