code: def bostonhousing():
      from tensorflow.keras.datasets import boston_housing
  
      (x_train, y_train), (x_test, y_test) = boston_housing.load_data()
  
      model = Sequential()
      model.add(
          Dense(1, input_shape=(x_train.shape[1],), activation="linear")
      )
      model.compile(
          optimizer="adam", loss="mse", metrics=["mse", "mae"]
      )
      learner = ktrain.get_learner(
          model,
          train_data=(x_train, y_train),
          val_data=(x_test, y_test),
      )
      learner.lr_find(max_epochs=5)  # use max_epochs until TF 2.4
      hist = learner.fit(0.05, 8, cycle_len=1, cycle_mult=2)
      learner.view_top_losses(n=5)
      learner.validate()
      return hist
  
imports: from unittest import TestCase, main, skip
  import testenv
  import ktrain
label_desc: Use image node_id 1 for calling a global function with example usage: bostonhousing() and returns: hist