Informal Neural Network Task Difficulty

Which binary classification task is considered easiest and therefore learnable with the fewest training examples?

According to ML Yearning, easier binary classification tasks require fewer training examples than harder binary classification tasks.

You will be able to learn _____ tasks with fewer training examples.

Match each binary classification task to its relative difficulty position in ML Yearning's ordered list (1 = easiest, 5 = hardest).

Order these five binary classification tasks from easiest (1) to hardest (5) as listed in ML Yearning.

Why does task difficulty matter when choosing which subtask to assign to a pipeline component, according to ML Yearning?

According to ML Yearning, classifying whether an image contains a Siamese cat is easier for a neural network than classifying whether an image was taken indoors or outdoors.

Each of the five example tasks in ML Yearning is a _____ image classification task: input an image and output either 0 or 1.

Match each task characteristic to the binary classification task it best describes from ML Yearning's five-task difficulty list.

Order the steps a practitioner should follow when applying ML Yearning's task-simplicity principle to select a pipeline component's task formulation.

Impact of Task Difficulty on Data Requirements

Selecting a Task Under Data Constraints

Relating Task Complexity to Data Volume