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Machine Learning (ML)

Machine Learning is a technique where algorithms learn from data to make predictions or decisions without being explicitly programmed for every possible scenario.

There are three main types of Machine Learning:

  • Supervised Learning – the model is trained using labelled data.
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Similar to teaching with flashcards: the model sees the input (question) and the correct output (answer), learning the pattern over time.

  • Unsupervised Learning – the model receives data without labels and must discover patterns or groupings on its own.
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Like giving students a pile of puzzle pieces and asking them to put it together without a guiding picture.

  • Reinforcement Learning – the model learns by interacting with an environment, receiving rewards or penalties.
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Think of training a puppy: it explores, gets positive or negative feedback, and adjusts its behaviour accordingly.

ML relies on large volumes of data to recognise patterns and improve performance over time.