from emnist import extract_training_samples

# Grab the data from the OpenML website
# X will be our images and y will be the labels
X, y = extract_training_samples('letters')

# Make sure that every pixel in all of the images is a value between 0 and 1
X = X / 255.

# Use the first 60000 instances as training and the neXt 10000 as testing
X_train, X_test = X[:60000], X[60000:70000]
y_train, y_test = y[:60000], y[60000:70000]

# There is one other thing we need to do, we need to
# record the number of samples in each dataset and the number of pixels in each image
X_train = X_train.reshape(60000, 784)
X_test = X_test.reshape(10000, 784)

print("Extracted our samples and divided our training and testing data sets")
fb14c264385f13e9933bdbe99c9013347595f3fb
<mask token>

<mask token>
print('Extracted our samples and divided our training and testing data sets')

<mask token>
X, y = extract_training_samples('letters')
X = X / 255.0
X_train, X_test = X[:60000], X[60000:70000]
y_train, y_test = y[:60000], y[60000:70000]
X_train = X_train.reshape(60000, 784)
X_test = X_test.reshape(10000, 784)
print('Extracted our samples and divided our training and testing data sets')

from emnist import extract_training_samples
X, y = extract_training_samples('letters')
X = X / 255.0
X_train, X_test = X[:60000], X[60000:70000]
y_train, y_test = y[:60000], y[60000:70000]
X_train = X_train.reshape(60000, 784)
X_test = X_test.reshape(10000, 784)
print('Extracted our samples and divided our training and testing data sets')

from emnist import extract_training_samples

# Grab the data from the OpenML website
# X will be our images and y will be the labels
X, y = extract_training_samples('letters')

# Make sure that every pixel in all of the images is a value between 0 and 1
X = X / 255.

# Use the first 60000 instances as training and the neXt 10000 as testing
X_train, X_test = X[:60000], X[60000:70000]
y_train, y_test = y[:60000], y[60000:70000]

# There is one other thing we need to do, we need to
# record the number of samples in each dataset and the number of pixels in each image
X_train = X_train.reshape(60000, 784)
X_test = X_test.reshape(10000, 784)

print("Extracted our samples and divided our training and testing data sets")