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mbadry1 committed Feb 3, 2018
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Expand Up @@ -273,7 +273,7 @@ Here are the course summary as its given on the course [link](https://www.course
- Because the update gate U is usually a small number like 0.00001, GRUs doesn't suffer the vanishing gradient problem.
- In the equation this makes C<sup><t></sup> = C<sup><t-1></sup> in a lot of cases.
- Shapes:
- a<sup><t></sup> shape is (NoOfHiddenNeurons + n<sub>x</sub>, 1)
- a<sup>\<t></sup> shape is (NoOfHiddenNeurons + n<sub>x</sub>, 1)
- c<sup><t></sup> is the same as a<sup><t></sup>
- c<sup>~<t></sup> is the same as a<sup><t></sup>
- u<sup><t></sup> is also the same dimensions of a<sup><t></sup>
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