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  3. Introduction to TensorFlow in Python

Exercise

Evaluating models

Two models have been trained and are available: large_model, which has many parameters; and small_model, which has fewer parameters. Both models have been trained using train_features and train_labels, which are available to you. A separate test set, which consists of test_features and test_labels, is also available.

Your goal is to evaluate relative model performance and also determine whether either model exhibits signs of overfitting. You will do this by evaluating large_model and small_model on both the train and test sets. For each model, you can do this by applying the .evaluate(x, y) method to compute the loss for features x and labels y. You will then compare the four losses generated.

Instructions

100 XP
  • Evaluate the small model using the train data.
  • Evaluate the small model using the test data.
  • Evaluate the large model using the train data.
  • Evaluate the large model using the test data.