What is the difference between supervised and unsupervised learning?
Experience Level: Junior
Tags: Machine learning
Answer
Supervised learning involves training a machine learning model on a labeled dataset, where the input data is paired with the correct output. The goal is to learn a mapping from the input to the output so that the model can make accurate predictions on new, unseen data.
Examples of supervised learning include
- image classification,
- speech recognition,
- regression analysis.
Unsupervised learning involves training a model on an unlabeled dataset, with the goal of discovering patterns or structure in the data.
Examples of unsupervised learning include
- clustering,
- dimensionality reduction,
- anomaly detection.
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