What trend should you expect in dev-set error as the training set gets larger?

True or False: Increasing the training set often reduces dev-set error when the model can benefit from more data.

More Training Data and Dev Error

Match each learning-curve term to its description.

Order the steps for creating a validation learning curve.

A team trains on 2,500 examples and sees 24% dev-set error. After adding 7,500 more training examples, what outcome should they expect?

True or False: Adding more training examples usually makes dev-set error worse.

What a Learning Curve Plots

Match each learning-curve pattern to its most likely interpretation.

Order the steps for deciding whether more training data is worth collecting based on a dev-set learning curve.

Why does validation error usually fall as the training set gets larger?

How a training-set increase should affect dev error

Effect of more training data on validation error