Documenting and evaluating a machine learning model
Lesson details
Learning outcome
I can create a model card to document a machine learning model.
Key learning points
- It is important to evaluate a machine learning model’s accuracy. A confusion matrix can be used to visualise this.
- Reporting a model’s accuracy improves accountability so we can be more open about mistakes and issues.
- A model card provides more information, improving accountability and demonstrates responsible practice.
Keywords
Accuracy - how many times a model makes a correct prediction
Accountability - taking responsibility for how a model behaves and being honest about its performance, limitations and potential impact on others
Model card - a short report on how a machine learning model works, how well the model performs and what people should know before using the model
Common misconception
Users of a machine learning application do not need to be aware of how accurate it is.
Model cards are good practice when developing machine learning applications. A model card is a short report on how a machine learning model works, how well the model performs and what people should know before using the model.
Teacher tip
The model card pupils create in this lesson could be used as an assessment piece for this unit.
Equipment
Pupils will need access to a physical device to capture data and a means of creating a data-driven application. Examples in this lesson use micro:bits and CreateAI https://oak.link/createai
Licence
Lesson video
Loading...
Prior knowledge starter quiz
6 Questions
Q1.What is a recognition point in a machine learning model?
Q2.What is the default recognition point in CreateAI?
Q3.Why might sound not always be the best feedback method?
Q4.What does the program flow refer to?
Q5. blocks can be used in MakeCode to program machine learning applications on a micro:bit.
Q6.A certainty value in machine learning is expressed as a .
Assessment exit quiz
6 Questions
Q1.What is a model card in machine learning?
Q2.A model card helps users understand a machine learning model’s purpose, accuracy and .
Q3.A confusion matrix visually represents how a model’s compare to actual values.
Q4.Why is accountability important in machine learning?
Q5.If a model correctly classifies 27 out of 30 test examples, what is its accuracy?
Q6.Match the term to the description.
how often a model makes correct predictions
a table showing correct and incorrect classifications
taking responsibility for a model's performance and fairness
a document explaining a model’s purpose, accuracy and limitations
To help you plan your 9 computing lesson on: Documenting and evaluating a machine learning model, download all teaching resources for free and adapt to suit your pupils' needs...
To help you plan your 9 computing lesson on: Documenting and evaluating a machine learning model, download all teaching resources for free and adapt to suit your pupils' needs.
The starter quiz will activate and check your pupils' prior knowledge, with versions available both with and without answers in PDF format.
We use learning cycles to break down learning into key concepts or ideas linked to the learning outcome. Each learning cycle features explanations with checks for understanding and practice tasks with feedback. All of this is found in our slide decks, ready for you to download and edit. The practice tasks are also available as printable worksheets and some lessons have additional materials with extra material you might need for teaching the lesson.
The assessment exit quiz will test your pupils' understanding of the key learning points.
Our video is a tool for planning, showing how other teachers might teach the lesson, offering helpful tips, modelled explanations and inspiration for your own delivery in the classroom. Plus, you can set it as homework or revision for pupils and keep their learning on track by sharing an online pupil version of this lesson.
Explore more key stage 3 computing lessons from the Machine learning using the micro:bit unit, dive into the full secondary computing curriculum, or learn more about lesson planning.