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typo in conv tutorial about calculating output size of conv layers

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bentrevett 2018-07-05 17:16:10 +01:00
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4 - Convolutional Sentiment Analysis.ipynb
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@ -117,7 +117,7 @@
"\n",
"![](https://i.imgur.com/gi1GaEz.png)\n",
"\n",
"In our case (and in the general case where the width of the filter equals the width of the \"image\"), our output will be a vector with number of elements equal to the height of the image (or lenth of the word) minus the height of the filter, $5-2=3$ in this case.\n",
"In our case (and in the general case where the width of the filter equals the width of the \"image\"), our output will be a vector with number of elements equal to the height of the image (or lenth of the word) minus the height of the filter plus one, $4-2+1=3$ in this case.\n",
"\n",
"This example showed how to calculate the output of one filter. Our model (and pretty much all CNNs) will have lots of these filters. The idea is that each filter will learn a different feature to extract. In the scenario of analysing text, we are hoping each of the **[2 x emb_dim]** filters will be looking for a certain bi-gram. \n",
"\n",