Learning Data Mining with Python - Second Edition

Getting the data

To start with, we will take our CIFAR images and create a dataset with them. Unlike previously, we are going to preserve the pixel structure—that is, in rows and columns. First, load all the batches into a list:

import osimport numpy as np data_folder = os.path.join(os.path.expanduser("~"), "Data", "cifar-10-batches-py")batches = [] for i in range(1, 6):    batch_filename = os.path.join(data_folder, "data_batch_{}".format(i))    batches.append(unpickle(batch_filename))     break

The last line, the break, is to test the code—this will drastically reduce the number of training examples, allowing you to quickly see if your code is working. I'll prompt you later to remove this line after you have tested that the code works.

Next, create ...