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To download the MNIST dataset, copy and paste the following code into the notebook and run it:.

%%time 
import pickle, gzip, urllib.request, json
import numpy as np

# Load the dataset
urllib.request.urlretrieve("http://deeplearning.net/data/mnist/mnist.pkl.gz", "mnist.pkl.gz")
with gzip.open('mnist.pkl.gz', 'rb') as f:
    train_set, valid_set, test_set = pickle.load(f, encoding='latin1')
print(train_set[0].shape)

The code does the following:

1. Downloads the MNIST dataset (mnist.pkl.gz) from the MNIST Database website to your notebook.

2. Unzips the file and reads the following datasets into the notebook’s memory:

   • train_set – You use these images of handwritten numbers to train a model.
   • valid_set – The XGBoost Algorithm uses these images to evaluate the progress of the model during training.
   • test_set – You use this set to get inferences to test the deployed model.

Next Step
Step 4.2: Explore the Training Dataset