MACHINE LEARNING
106403This page collects 71 machine learning questions taken from 3 BEU semester 4 papers, 2022 to 2025 — about 24 questions in a typical paper. They are sorted into the 10 modules of the syllabus, so you can revise a topic across every year at once instead of working through papers one at a time. 69 of them have a worked solution.
What these papers actually ask
Module 3: Classification Algorithms is the heaviest module in this archive at 28% of every question recorded, across 2 of 3 papers. Together with Unit 3: Classification & Regression, the two account for 42% of the archive.
Module 3: Classification Algorithms20 questions · 28% · 2 of 3 papers
Unit 3: Classification & Regression10 questions · 14% · 1 of 3 papers
Module 1: Introduction8 questions · 11% · 2 of 3 papers
Module 2: Linear Models and Bayesian Learning7 questions · 9.9% · 2 of 3 papers
Unit 1: Introduction6 questions · 8.5% · 1 of 3 papers
Module 4: Clustering, K-means, K-medoids, Density-based Hierarchical, Spectral .5 questions · 7.0% · 2 of 3 papers
Unit 4: Advanced Topics & Clustering5 questions · 7.0% · 1 of 3 papers
Unit 2: Statistical Decision Theory4 questions · 5.6% · 1 of 3 papers
Module 5: Probabilistic & Reinforcement Methods3 questions · 4.2% · 2 of 3 papers
Unit 5: Specialized Learning Theories3 questions · 4.2% · 1 of 3 papers
How the marks are split
Questions in this archive carry 5 different mark values. The most common is the 7-mark question, with 38 of them recorded — worth knowing before you decide how much depth to practise at.
2 marks · 264 marks · 17 marks · 3810 marks · 114 marks · 5
Papers
By module
Module 1: Introduction8Module 2: Linear Models and Bayesian Learning7Module 3: Classification Algorithms20Module 4: Clustering, K-means, K-medoids, Density-based Hierarchical, Spectral .5Module 5: Probabilistic & Reinforcement Methods3Unit 1: Introduction6Unit 2: Statistical Decision Theory4Unit 3: Classification & Regression10Unit 4: Advanced Topics & Clustering5Unit 5: Specialized Learning Theories3