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.
Este exercicio faz parte do curso
Machine Learning for Finance in Python
Instruções do exercicio
- Plot the losses (
'loss') fromhistory.history. - Set the title of the plot as the last loss from
history.history, and round it to 6 digits.
exercicio interativo prático
Tente este exercicio completando este código de exemplo.
# Plot the losses from the fit
plt.plot(____)
# Use the last loss as the title
plt.title('loss:' + str(round(____, 6)))
plt.show()