At its core, machine learning works by training algorithms on large datasets. These algorithms learn from examples and gradually adjust their internal parameters to minimize errors.
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There are three main types of machine learning: supervised learning, unsupervised learning, and reinforcement learning. Supervised learning uses labeled data to make predictions, while unsupervised learning finds hidden patterns in unlabeled data. Reinforcement learning, on the other hand, trains models through rewards and penalties based on their actions.