The Dogs vs. Cats dataset that you'll use isn't packaged with Keras. It was made avail- able by Kaggle as part of a computer-vision competition in late 2013, back when convnets weren't mainstream. You...

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Extracted text: The Dogs vs. Cats dataset that you'll use isn't packaged with Keras. It was made avail- able by Kaggle as part of a computer-vision competition in late 2013, back when convnets weren't mainstream. You can download the original dataset from www.kaggle .com/c/dogs-vs-cats/data (you'll need to create a Kaggle account if you don't already have one-don't worry, the process is painless). The pictures are medium-resolution color JPEGS. Figure 5.8 shows some examples. Figure 5.8 Samples from the Dogs vs. Cats dataset. Sizes weren't modified: the samples are heterogeneous in size, appearance, and so on. Unsurprisingly, the dogs-versus-cats Kaggle competition in 2013 was won by entrants who used convnets. The best entrics achieved up to 95% accuracy. In this example, you'll get fairly close to this accuracy (in the next section), even though you'll train your models on less than 10% of the data that was available to the competitors. This dataset contains 25,000 images of dogs and cats (12,500 from each class) and is 543 MB (compressed). After downloading and uncompressing it, you'll create a new dataset containing three subsets: a training set with 1,000 samples of each class, a vali- dation set with 500 samples of each class, and a test set with 500 samples of each class.