Login using Social Account
     Continue with GoogleLogin using your credentials
Let us load the fashion mnist dataset from Keras data sets.
We shall then split the data into train, validation, and test parts.
Load the train and test data using keras.datasets.fashion_mnist.load_data()
.
(X_train_full, y_train_full), (X_test, y_test) = << your code comes here >>
Scale the X_train_full
and X_test
data sets with 255
.
X_train_full = X_train_full.astype(np.float32) / 255
X_test = X_test.astype(np.float32) / 255
Slice the X_train_full
, such that the last 5000 samples form the validation data X_valid
and the remaining samples form the train data X_train
.
X_train, X_valid = << your code comes here >>[:-5000], << your code comes here >>[-5000:]
Similarly, slice the y_train_full
, such that the last 5000 samples form the validation data labels y_valid
and the remaining samples form the train data labels y_train
.
y_train, y_valid = << your code comes here >>[:-5000], << your code comes here >>[-5000:]
Taking you to the next exercise in seconds...
Want to create exercises like this yourself? Click here.
Note - Having trouble with the assessment engine? Follow the steps listed here
Loading comments...