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Plot losses

Once we've fit a model, we usually check the training loss curve to make sure it's flattened out. The history returned from model.fit() is a dictionary that has an entry, 'loss', which is the training loss. We want to ensure this has more or less flattened out at the end of our training.

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Machine Learning for Finance in Python

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Anleitung zur Übung

  • Plot the losses ('loss') from history.history.
  • Set the title of the plot as the last loss from history.history, and round it to 6 digits.

Interaktive Übung

Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.

# Plot the losses from the fit
plt.plot(____)

# Use the last loss as the title
plt.title('loss:' + str(round(____, 6)))
plt.show()
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