How the K Nearest Neighbours Algorithm Works

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Supervised learning is a core part of machine learning, and something you’ll probably use quite a lot. This lesson is part one of the module on supervised learning, in which you’ll learn about exactly what supervised learning is and what its capable of, before moving into more detail on the nearest neighbors algorithm.

Part two of supervised learning can be found here and covers hyperparameters, distance functions, similarity measures, logistic regression, the method and workflow of machine learning and evaluation, and the train-test split.

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Michael Burgess, opens in a new tab
Principal Technologist for Machine Learning
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Michael began programming as a young child, and after freelancing as a teenager, he joined and ran a web start-up during university. Around studying physics and after graduating, he worked as an IT contractor: first in telecoms in 2011 on a cloud digital transformation project; then variously as an interim CTO, Technical Project Manager, Technical Architect and Developer for agile start-ups and multinationals.

His academic work on Machine Learning and Quantum Computation furthered an interest he now pursues as QA's Principal Technologist for Machine Learning. Joining QA in 2015, he authors and teaches programmes on computer science, mathematics and artificial intelligence; and co-owns the data science curriculum at QA.

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