For this example, we will use the dog versus cat dataset from Kaggle that was provided for the infamous Dogs versus Cats classification problem as a playground competition with kernels enabled. The dataset can be downloaded from https://www.kaggle.com/c/dogs-vs-cats-redux-kernels-edition/data.
The train folder contains 25,000 images of dogs and cats. Each image in this folder has the label as part of the filename. The test folder contains 12,500 images, named according to a numeric ID. For each image in the test set, you should predict a probability that the image is a dog (1 = dog, 0 = cat); that is, a binary classification problem. For this example, there are three Python scripts.
