How to revise Machine Learning Practice
Machine Learning Practice questions reward clear reasoning as well as a final answer. This revision guide is a starting point for using the available papers; it is not the official syllabus or a promise about future exams.
Revision focus
Data preparation; validation; leakage; feature pipelines; evaluation
Useful prior knowledge
Python, tabular data handling and basic supervised learning
Common mistakes
Fitting preprocessing to the full dataset before splitting it
Use these papers effectively
Trace which data each pipeline step can see. Explain how the proposed validation setup represents genuinely unseen observations. After checking a solution, solve the question again without looking and record the specific step you missed.
Revision guidance only. Check your current official course materials for the assessed syllabus.