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Section checkpoint · 01

ML Foundations

Use this short test to check whether the main ideas from the section are connected in your mind. A strong score means you can recognise the concepts; revisit linked lessons when an answer feels uncertain.

5questionsTarget: 4/5 or better

Question 11 point

Which concept is most appropriate for this situation: You need to apply the idea taught in “Machine Learning Workflow” and explain how its input is transformed into a valid output.

Supervised and Unsupervised LearningParameters vs HyperparametersTraining Validation and InferenceMachine Learning Workflow

Question 21 point

Which concept is most appropriate for this situation: You need to apply the idea taught in “Supervised and Unsupervised Learning” and explain how its input is transformed into a valid output.

Machine Learning WorkflowSupervised and Unsupervised LearningParameters vs HyperparametersFeatures Targets and Examples

Question 31 point

Which concept is most appropriate for this situation: You need to apply the idea taught in “Features Targets and Examples” and explain how its input is transformed into a valid output.

GeneralisationTraining Validation and InferenceFeatures Targets and ExamplesSupervised and Unsupervised Learning

Question 41 point

Which concept is most appropriate for this situation: You need to apply the idea taught in “Training Validation and Inference” and explain how its input is transformed into a valid output.

Supervised and Unsupervised LearningTraining Validation and InferenceGeneralisationFeatures Targets and Examples

Question 51 point

Which concept is most appropriate for this situation: You need to apply the idea taught in “Generalisation” and explain how its input is transformed into a valid output.

GeneralisationParameters vs HyperparametersMachine Learning WorkflowTraining Validation and Inference