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MLPs for CTR

In this exercise, you will evaluate both the accuracy score and AUC of the ROC curve for a basic MLP model on the ad CTR dataset. Remember to standardize the features before splitting into training and testing!

X is available as the DataFrame with features, and y is available as a DataFrame with target values. Both sklearn and pandas as pd are also available in your workspace.

This exercise is part of the course

Predicting CTR with Machine Learning in Python

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Scale features and split into training and testing
X_scaled = ____().____(X)
X_train, X_test, y_train, y_test = ____(
  X_scaled, y, test_size = .2, random_state = 0)
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