April 2020
Intermediate to advanced
330 pages
7h 44m
English
Content preview from Hands-On Deep Learning with R
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Enhancing the model with additional layers
In this section, we add two important layers: the convolution layer, and pooling layer:
- Before beginning, we make one small change to the data structure. We will add a fourth dimension that is a constant value. We add the extra dimension using the following code:
dim(train) <- c(nrow(train), 28, 28, 1) dim(test) <- c(nrow(test), 28, 28, 1)
When we make this change, we can see the added dimension for these data objects in the Environment pane, which will look like the following image:
We make this change to the structure because it is a requirement of modeling a CNN using keras.
- As before, the ...
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