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How machines learn from data

From Mock A · Paper 1: Written examination
41 mark
A model is trained to recognise spam emails. In the training data, what is the label?
From Mock A · Paper 1: Written examination
13(a)2 marks
A school wants to train a machine learning model to predict whether a student will need extra maths support. For each past student it has: - hours of homework per week - last maths test score - attendance (%) - whether they needed extra support (Yes/No) Identify the features and the label in this data.
From Mock A · Paper 1: Written examination
13(b)3 marks
Describe how the data in 13(a) would be used to train the model.
From Mock A · Paper 1: Written examination
13(c)2 marks
The school only has data from one class of 20 students. Explain why this may not produce a reliable model.
From Mock A · Paper 2: Combined internal assessment (project)
2(b)4 marks
Describe your data plan: what data you need, where it will come from, how much you need and (if relevant) the features and labels.
From Mock B · Paper 1: Written examination
51 mark
What does pattern recognition mean in machine learning?
From Mock B · Paper 1: Written examination
11(a)2 marks
A music streaming app recommends songs to its users. State two types of data the app could collect about a user to make recommendations.
From Mock B · Paper 1: Written examination
11(b)3 marks
Explain how the app could use machine learning to recommend new songs.
From Mock B · Paper 1: Written examination
13(c)3 marks
The school decides to train a machine learning chatbot on past helpdesk messages. Describe how the data should be prepared before training.
From Mock B · Paper 1: Written examination
15(d)2 marks
Explain why the images used to train this model should include fruit photographed in different lighting and from different angles.
From Mock B · Paper 2: Combined internal assessment (project)
2(b)4 marks
Describe your data plan: what data you need, where it will come from, how much you need and (if relevant) the features and labels.
From Mock C · Paper 1: Written examination
61 mark
In machine learning, what is a feature?
From Mock C · Paper 1: Written examination
11(a)2 marks
An AI model is trained on 50 000 chest X-rays to detect pneumonia. The X-rays are labelled. Explain what "labelled" means in this context.
From Mock C · Paper 2: Combined internal assessment (project)
2(b)4 marks
Describe your data plan: what data you need, where it will come from, how much you need and (if relevant) the features and labels.
From Mock D · Paper 1: Written examination
61 mark
Which of these is part of cleaning data before training a model?
From Mock D · Paper 1: Written examination
11(a)2 marks
An email provider uses machine learning to filter spam. State two features of an email that the model could use.
From Mock D · Paper 1: Written examination
13(d)2 marks
State one suitable way to visualise this temperature data and explain why it is suitable.
From Mock D · Paper 2: Combined internal assessment (project)
2(b)4 marks
Describe your data plan: what data you need, where it will come from, how much you need and (if relevant) the features and labels.
From Mock E · Paper 1: Written examination
61 mark
Why should data be cleaned before it is used to train a model?
From Mock E · Paper 1: Written examination
11(e)1 mark
State one other feature the shop could add to improve the clustering.
From Mock E · Paper 2: Combined internal assessment (project)
2(b)4 marks
Describe your data plan: what data you need, where it will come from, how much you need and (if relevant) the features and labels.
From Mock F · Paper 1: Written examination
51 mark
What is labelled data?
From Mock F · Paper 1: Written examination
11(a)1 mark
A football academy wants a model to predict whether a player will be injured this season. Part of its data is shown.
Player30 m sprint (s)Distance per match (km)Injured last seasonInjured this season
P14.310.2NoNo
P29.8YesNo
P3−3.211.0YesYes
P44.110.6NoNo
P14.310.2NoNo
State the label in this data.
From Mock F · Paper 1: Written examination
11(b)2 marks
Explain why the player's name should not be used as a feature.
From Mock F · Paper 1: Written examination
11(c)4 marks
Identify two problems with the data in 11(a) and explain how each should be dealt with before training.
From Mock F · Paper 2: Combined internal assessment (project)
2(b)4 marks
Describe your data plan: what data you need, where it will come from, how much you need and (if relevant) the features and labels.
Score 0 / 61 · 0 of 26 marked

This paper is written by Plasmo in the style of the LRN GCSE Artificial Intelligence exam. It is not a past paper and is not produced or endorsed by the exam board.

How machines learn from data Exam Questions: LRN GCSE Artificial Intelligence | Plasmo