Machine learning
Algorithms that infer a rule or pattern from data rather than being programmed with one. A model is judged on how well it performs on data it has not seen.
Where you will meet it
Machine learning appears in 3 learning outcomes on the CFA syllabus. A few of them:
- Explain what is meant by machine learning, artificial intelligence and big data
“Machine learning is the practical subset that infers a rule from data rather than being given one: supervised learning trains on labelled examples, unsupervised learning looks for structure in unlabelled data, and deep learning stacks layers to capture relationships too complex to specify in advance.”
- Recognise the stages of a data analysis project and explain each one
“A structured-data machine learning project runs in five steps: conceptualise the modelling task (what the output is and how it will be used), collect the data, prepare and wrangle them, explore them, and train the model.”
- Explain deep, supervised and unsupervised learning and how investment managers use them
“Machine learning finds patterns in data without the analyst specifying the model's form in advance.”
Practise it
Practise machine learning until it is automatic: questions that explain every wrong option.
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