Actual cats and dogs
We've demonstrated our new tools on the notMNIST dataset, which was helpful as it served to provide a comparison to our earlier simpler network setup. Now, let's progress to a more difficult problem—actual cats and dogs.
We'll utilize the CIFAR-10 dataset. There will be more than just cats and dogs, there are 10 classes—airplanes, automobiles, birds, cats, deer, dogs, frogs, horses, ships, and trucks. Unlike the notMNIST set, there are two major complexities, which are as follows:
- There is far more heterogeneity in the photos, including background scenes
- The photos are color
We have not worked with color datasets before. Luckily, it is not that different from the usual black and white dataset—we will just add another dimension. Recall that our previous 28x28 images were flat matrices. Now, we'll have 32x32x3 matrices - the extra dimension represents a layer for each red, green, and blue channels. This does make visualizing the dataset more difficult, as stacking up images...
